DETAILED ACTION
Remarks
Claims 1-20 have been examined and rejected. This Office action is responsive to the amendment filed on 07/13/2026, which has been entered in the above identified application.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1 and 11
Step 1: Claims 1 and 11 recite a system and a method; therefore, they are directed to the statutory categories of a machine and a method.
Step 2A Prong 1: The claims recite, inter alia:
the content generation model (i) analyzes information to identify individual adventures of individual users, and (ii) generates individual narratives for the individual adventures from the content of the content domains; Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of analyzing information to generate a narrative, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper.
determine, based on the pieces of information, aspect values that define the aspects of the transportation and the aspects of the experience occurrences; input the aspect values that define the aspects of the transportation and the aspects of the experience occurrences to the content generation model so that the content generation model determines the adventure of the user and generates, based on the aspect values, a narrative that features the aspects of the experience occurrences and one or more of the aspects of the transportation to represent the adventure of the user; obtain, from the content generation model, the narrative; Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of analyzing information to generate a narrative, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The additional elements of “A system configured to generate narratives based on a comprehensive set of experiences of users, the system comprising”, “electronic storage that stores (a) content domains and (b) a content generation model, wherein the content domains include content for subjects of storylines, affiliations between the subjects, descriptions of settings, and anecdotes of the storylines”, “using generative artificial intelligence”, “one or more processors configured by machine-readable instructions to”, “A method to generate narratives based on a comprehensive set of experiences of users, the method comprising”, and ”managing in electronic storage” amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h). The claimed computer components are recited at a high level of generality and are merely invoked as tool to perform the abstract idea. The additional elements of “receive a user authorization to obtain, from one or more information sources, pieces of information that define transportation and experience occurrences associated with a user, the pieces of information forming an adventure of the user, wherein: aspects of the transportation include one or more of a transportation mode, a start point, an end point, a travel time, a class, a complimentary good, or a complimentary service, and aspects of the experience occurrences include an occurrence type, one or more of the content domains, one or more companions in the occurrence, a time length of the occurrence, a wait time, one or more purchases, and/or a venue of the occurrence”, and “effectuate presentation of the narrative to the user” amount to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)). Even when viewed in combination, these additional element do not integrate the abstract idea into a practical application and the claims are thus directed to the abstract idea.
Step 2B: The claims do not contain significantly more than the judicial exception. “A system configured to generate narratives based on a comprehensive set of experiences of users, the system comprising”, “electronic storage that stores (a) content domains and (b) a content generation model, wherein the content domains include content for subjects of storylines, affiliations between the subjects, descriptions of settings, and anecdotes of the storylines”, “using generative artificial intelligence”, “one or more processors configured by machine-readable instructions to”, “A method to generate narratives based on a comprehensive set of experiences of users, the method comprising”, and ”managing in electronic storage” amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements of “receive a user authorization to obtain, from one or more information sources, pieces of information that define transportation and experience occurrences associated with a user, the pieces of information forming an adventure of the user, wherein: aspects of the transportation include one or more of a transportation mode, a start point, an end point, a travel time, a class, a complimentary good, or a complimentary service, and aspects of the experience occurrences include an occurrence type, one or more of the content domains, one or more companions in the occurrence, a time length of the occurrence, a wait time, one or more purchases, and/or a venue of the occurrence”, and “effectuate presentation of the narrative to the user” amounts to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)), and is a well-understood, routine, conventional activity (see MPEP § 2106.05(d); “Receiving or transmitting data over a network”). Nothing in the claims provides significantly more than that abstract idea. As such, the claims are ineligible.
Claims 2-10 and 12-20
Step 1: Claims 2-10 and 12-20 recite systems and methods; therefore, they are directed to the statutory categories of a machine and a method.
Step 2: claims 2-10 and 12-20 merely narrow the previously recited abstract idea limitations. For the reasons described above with respect to claims 1 and 11, this judicial exception is not meaningfully integrated into a practical application, or significantly more than the abstract idea. The claims disclose similar limitations described for the independent claims above and do not provide anything more than the mental processes that are practically capable of being performed in the human mind with the assistance of pen and paper and mathematical concepts that are achievable through mathematical computation.
Claims 2 and 12 further recite the additional elements of “wherein the user authorization includes input via a client computing platform, wherein the input indicates an authorization to obtain all the pieces of information or particular ones of the pieces of information”. These elements amount to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)), and is a well-understood, routine, conventional activity (see MPEP § 2106.05(d); “Receiving or transmitting data over a network”).
Claims 3 and 13 further recite the additional elements of “wherein the client computing platform is associated with the user, or is associated with and located at the venue”. These elements amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)).
Claims 4 and 14 further recite the additional elements of “wherein the user authorization includes: recognition device information for recognition devices, recognizable features, or identification of the one or more companions”. These elements amount to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)), and is a well-understood, routine, conventional activity (see MPEP § 2106.05(d); “Receiving or transmitting data over a network”).
Claims 5 and 15 further recite the additional elements of “wherein the narrative includes a long form video, short form video, a collection of video clips and photos, or a story book”. These elements amount to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)), and is a well-understood, routine, conventional activity (see MPEP § 2106.05(d); “Receiving or transmitting data over a network”).
Claims 6 and 16 further recite the additional elements of “wherein the user authorization includes the recognition device information for the recognition devices” and “wherein the content generation model identifies the individual adventures of the individual users based on the one or more timestamps, image recognition, and/or location information based on the recognition devices of the users”. Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of identifying based on time, images, or location, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper. The additional elements of “wherein individual ones of the pieces of information are associated with one or more timestamps“ amounts to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)).
Claims 7 and 17 further recite the additional elements of “wherein information sources of the one or more information sources include retailers, accommodation providers, food and beverage providers, and event providers”. These elements amount to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)), and is a well-understood, routine, conventional activity (see MPEP § 2106.05(d); “Receiving or transmitting data over a network”).
Claims 8 and 18 further recite the additional elements of “wherein the pieces of information include one or more of purchase records, captured images and/or videos, scanned event admissions, reservation records, or itineraries”. These elements amount to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)), and is a well-understood, routine, conventional activity (see MPEP § 2106.05(d); “Receiving or transmitting data over a network”).
Claims 9 and 19 further recite the additional elements of “wherein effectuating presentation of the narrative includes transmitting the narrative via one or more of e-mail, text messaging, social media platforms, or close range wireless communication”. These elements amount to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)), and is a well-understood, routine, conventional activity (see MPEP § 2106.05(d); “Receiving or transmitting data over a network”).
Claims 10 and 20 further recite the additional elements of “wherein the occurrence type includes an experience type or an interaction type”. These elements amount to insignificant extra-solution activity in the form of mere data gathering and output (see MPEP § 2106.05(g)), and is a well-understood, routine, conventional activity (see MPEP § 2106.05(d); “Receiving or transmitting data over a network”).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-6, 8, 10-16, 18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Subramanian et al. (US 20150168162 A1, published 06/18/2015), hereinafter Subramanian, in view of Kasina (US 20180150444 A1, published 05/31/2018)
Regarding claim 1, Subramanian teaches the claim comprising:
A system configured to generate narratives based on a comprehensive set of experiences of users, the system comprising (Subramanian 1-6; A system and method of the subject technology automatically generates an electronic journal of a series of events based on input from data sources already used to record the series of events; [0004], generating a chronological storyline representative of the one or more travel events; [0027], data manager 101 may determine a confidence level that two or more users are on a joint adventure; claim 7, generating a narrative associated with the one or more travel events, the narrative including sequentially displaying at least a portion of the one or more text messages apart from the interactive map):
electronic storage that stores (a) content domains and (b) a content generation model, wherein the content domains include content for subjects of storylines, affiliations between the subjects, descriptions of settings, and anecdotes of the storylines, wherein the content generation model (i) analyzes information to identify individual adventures of individual users, and (ii) generates individual narratives for the individual adventures from the content of the content domains (Subramanian 1-6; [0014], a user on a trip through the Himalaya mountains may, at certain times, take digital photos, videos, and post messages to a blog or social network during the trip; [0016], FIG. 1 is an exemplary diagram of a system for automatically generating an electronic journal, including a user interface and a data manager; [0017], Other data sources operably connected to data manager 101 may include a remote server 105 (for example, a file server, data cloud, database, web-blog, web-service, or the like), a social network 106 (for example, at Facebook, Twitter, Google Buzz, and the like); [0019], data manager 101 may be configured to aggregate recorded data that is collected into a series of events that visually portrays a user's activities along a travel route. In this regard, the received GPS location data may include timestamp data that may be associated with timestamp data from the other collected data (for example, digital pictures, video, text messages, blog posts, and the like) recorded at specific points along a route over a period of time. From this data, data manager 101 may generate a virtual trail of location points with each point being associated with one or more photos, videos, text messages, blog posts, or the like; [0021], the collected data is compiled to generate an electronic journal 201 having a format of a chronological story; a condensed blog 208 may also be displayed in connection with map 202; [0023], an event 204 may be determined by comparing collected data with a respective cluster of data having similar features; one or more photos may be compared to determine whether they are substantially similar using color patterns and/or color comparisons. Similar photos may then be included as part of an event 204; [0024], System 100 may also be configured to analyze GPS information to determine a mode of transit, and then include that mode of transit in the generation of journal 102, for example, its text and/or its formatting; [0025], Data manager 101 may be further configured to include, for example, in the generation of text, reverse geocodes determined from comparing the GPS track to known geographical locations; [0027], data manager 101 may determine a confidence level that two or more users are on a joint adventure; claim 7, generating a narrative associated with the one or more travel events, the narrative including sequentially displaying at least a portion of the one or more text messages apart from the interactive map; [0032], In one aspect, computer 501 may display a user interface 507 (for example, user interface 108) to be used by a user 508. User interface 507 may be used to upload and/or integrate a variety of recorded data (including, for example, digital photos, videos, GPS tracks, text messages, blog posts, social network posts, check-in applications, and the like));
one or more processors configured by machine-readable instructions to (Subramanian 1-6; [0034], FIG. 6 is a diagram illustrating an exemplary server system for automatically generating an electronic journal, including a processor; [0035], Processor 601 may be configured to execute code or instructions to perform the operations and functionality described herein):
receive a user authorization to obtain, from one or more information sources, pieces of information that define transportation and experience occurrences associated with a user, the pieces of information forming an adventure of the user (Subramanian 1-6; [0017], Other data sources operably connected to data manager 101 may include a remote server 105 (for example, a file server, data cloud, database, web-blog, web-service, or the like), a social network 106 (for example, at Facebook, Twitter, Google Buzz, and the like), online picture storage 107 (for example, Picasa, Flickr, or the like), and/or other systems where data has previously been stored and/or uploaded for other purposes; data manager 101 may collect GPS location data recorded by a GPS-enabled data device 103, and further integrate with a social network to collect data that was posted to the social network over a period of time. In one aspect, a user may set parameters at user interface 108 to configure data manager 101 to only collect data over a predetermined time frame (for example, May 17-19), and/or to only collect data that is associated with a particular subject or tag. Once collected, the GPS location data and other data may then be combined by data manager 101 to generate electronic journal 102; [0032], computer 501 may display a user interface 507 (for example, user interface 108) to be used by a user 508. User interface 507 may be used to upload and/or integrate a variety of recorded data (including, for example, digital photos, videos, GPS tracks, text messages, blog posts, social network posts, check-in applications, and the like). In one aspect, a data source selection screen 509 is displayed by user interface 507 and may include a selectable menu for the selection of a data source; [0033], Parameters may be set at user interface 507 for configuring the system on how data is collected and integrated with system 500 (and/or, for example, data manager 101). For example, a user may configure the cloud to automatically receive data, including a predetermined meta-data tag, when posted to a social network or other online image and/or video host; [0042], appropriate efforts can be taken to protect a user's privacy and other rights. For example, collection and use of location data may be on an opt-in basis so that data is not collected at all unless the user has granted permission, with the location data stored and handled in a secure manner. When collected, the location and other data can be used according to user preferences and/or permissions. For example, sharing of the location data and information derived from the location data (for example, the storyline and/or journal created by the subject technology) may be controlled by the user),
wherein: aspects of the transportation include one or more of a transportation mode, a start point, an end point, a travel time, a class, a complimentary good, or a complimentary service (Subramanian 1-6; [0024], System 100 may also be configured to analyze GPS information to determine a mode of transit, and then include that mode of transit in the generation of journal 102, for example, its text and/or its formatting. In one aspect, a GPS track may determine a speed of travel, elevation, whether the user is ascending or descending, and/or method of travel (for example, by boat, land, or by air). For example, on detecting a consistent range of speed over a certain land location (for example, over a trail or rough terrain), data manager 101 may determine the trip was likely to be a bicycle trip. Data manager 101 may then include in journal 102 terms like "ride", "rest stop", "sprint", "climb", and/or "decent" to describe parts of the route. In another example, if the range of speed is at a walking speed through a national park, terms such as, for example, "hike" and "trail" may be used, reserving "climb" for much steeper ascents. In some aspects, journal 102 may include an elevation profile (for example, for hilly terrain). If the trip is determined to be by air, train, or boat, system 100 may attempt to access a known network location (for example, a travel service) to match the GPS track to a known flight, train or vessel having the same or substantially similar route, and include information relevant to the detected transportation. For example, if the trip is determined to match a known path of a cruise ship, the name and photo of the cruise ship may be included as part of journal 102; [0029], a travel route and a travel period is determined from the GPS data. The travel route may include a virtual trail of location points (for example, virtual travel route 203), and the travel period may be determined from the starting time and ending time of the travel route; claim 8, determining a mode of transportation from the location data; and automatically including text related to the mode of transportation with the narrative),
and aspects of the experience occurrences include an occurrence type, one or more of the content domains, one or more companions in the occurrence, a time length of the occurrence, a wait time, one or more purchases, and/or a venue of the occurrence (Subramanian 1-6; [0014], the data may be automatically assembled into a chronological series of events that visually portrays a user's activities along a travel route, together with text, pictures and video; [0020], hovering a pointing device over a representation of an event 204 may cause interactive map 202 to activate and display a dialog 205, including one or more image or video thumbnails 206 and/or text associated with event 204; [0023], an event 204 may be determined by comparing collected data with a respective cluster of data having similar features. For example, an event 204 may be determined by one or more data having a similar meta-data (for example, timestamps within a certain delta of each other, captured substantially at the same location, or the like). In another example, an event may be inferred by clusters of photos and/or videos taken of the same subject (for example, determined by computer-enabled image recognition and/or comparison processes); an event may be created and information about the landmark may be retrieved (for example, from a database or known online storage location) and included as part of the event; [0025], In generating a chronological story for a bicycling trip, a day trip may be characterized as "a ride around Lake Merced" or "a ride up Mount Tam." A multi-week bike tour might be characterized as "a tour from Seattle to San Diego," and an individual day might be presented as "Day 3: Astoria to Cape Lookout State Park." The characterizations may be included in an event 204, or may characterize a series of events 204 or a group of activities over a certain time period, or the like; [0027], data manager 101 may determine a confidence level that two or more users are on a joint adventure; If common points A, D, and G were visited at substantially the same time, an initial confidence level may be determined that both users were on a joint adventure; [0030], the image data is correlated with the travel route and the travel period to generate one or more travel events occurring during the travel period. In one aspect, this may be done by matching a timestamp associated with a digital picture to a timestamp associated with a GPS location data point);
determine, based on the pieces of information, aspect values that define the aspects of the transportation and the aspects of the experience occurrences; input the aspect values that define the aspects of the transportation and the aspects of the experience occurrences to the content generation model so that the content generation model determines the adventure of the user and generates, based on the aspect values, a narrative that features the aspects of the experience occurrences and one or more of the aspects of the transportation to represent the adventure of the user; obtain, from the content generation model, the narrative; and effectuate presentation of the narrative to the user (Subramanian 1-6; [0014], the data may be automatically assembled into a chronological series of events that visually portrays a user's activities along a travel route, together with text, pictures and video; [0019], In some aspects, data manager 101 may be configured to aggregate recorded data that is collected into a series of events that visually portrays a user's activities along a travel route; [0020], FIG. 2 is an exemplary diagram of an automatically generated electronic publication according to one aspect of the subject technology. In the depicted example, an electronic journal 201 (for example, in an online format) is generated to include an interactive map 202, with a virtual travel route 203 superimposed on interactive map 202. At one or more points along route 203, electronic journal 201 may include a collection of notes, pictures, and or other data arranged as events 204. In one aspect, hovering a pointing device over a representation of an event 204 may cause interactive map 202 to activate and display a dialog 205, including one or more image or video thumbnails 206 and/or text associated with event 204. In one aspect, dialog 205 may include one or more buttons 207 for moving through a series of images or the like within dialog 205. In another aspect, selecting dialog 205 may display a page of details associated with event 205. For example, clicking on dialog 205 with a mouse may cause a webpage to appear that includes all recorded data associated with event 204 in a blog format; [0021], the collected data is compiled to generate an electronic journal 201 having a format of a chronological story, and the chronological story displayed as part of, or in connection with, an interactive map 202; condensed blog 208 may be organized chronologically by event 204 and displayed on a side and apart from map 202, and such that the contents of events 204 are sequentially listed to depict a storyline associated with virtual travel route 203; [0024], System 100 may also be configured to analyze GPS information to determine a mode of transit, and then include that mode of transit in the generation of journal 102, for example, its text and/or its formatting. In one aspect, a GPS track may determine a speed of travel, elevation, whether the user is ascending or descending, and/or method of travel (for example, by boat, land, or by air). For example, on detecting a consistent range of speed over a certain land location (for example, over a trail or rough terrain), data manager 101 may determine the trip was likely to be a bicycle trip. Data manager 101 may then include in journal 102 terms like "ride", "rest stop", "sprint", "climb", and/or "decent" to describe parts of the route. In another example, if the range of speed is at a walking speed through a national park, terms such as, for example, "hike" and "trail" may be used, reserving "climb" for much steeper ascents. In some aspects, journal 102 may include an elevation profile (for example, for hilly terrain). If the trip is determined to be by air, train, or boat, system 100 may attempt to access a known network location (for example, a travel service) to match the GPS track to a known flight, train or vessel having the same or substantially similar route, and include information relevant to the detected transportation. For example, if the trip is determined to match a known path of a cruise ship, the name and photo of the cruise ship may be included as part of journal 102; [0030], In step 404, image data is extracted from the one or more digital pictures. The image data may include one or more timestamps, each corresponding to a respective picture. In step 405, the image data is correlated with the travel route and the travel period to generate one or more travel events occurring during the travel period. In one aspect, this may be done by matching a timestamp associated with a digital picture to a timestamp associated with a GPS location data point. In another aspect, this may be done by determining that the timestamps of a plurality of images fall within substantially the same time period, and then matching the time period with one or more GPS location data points; claim 7, generating a narrative associated with the one or more travel events, the narrative including sequentially displaying at least a portion of the one or more text messages apart from the interactive map; claim 8, determining a mode of transportation from the location data; and automatically including text related to the mode of transportation with the narrative)
However Subramanian fails to expressly disclose generates individual narratives for the individual adventures from the content domains using generative artificial intelligence. In the same field of endeavor, Sahay teaches:
generates individual narratives for the individual adventures from the content domains using generative artificial intelligence (Kasina Figs. 1-15; [0035], FIG. 1 shows a system 102 for constructing a textual narrative based on a set of images. In one example, an end user captures the set of images in the course of visiting one or more locations for any purpose. For example, the end user may capture the images in the course of a vacation to the location(s). The system 102 automatically (or semi-automatically) constructs a narrative which describes the images in a cohesive manner; [0037], an image capture device can also store any type of supplemental information that is associated with a captured image. For example, an image capture device can store position information which reflects the location at which an image has been captured. In addition, or alternatively, an image capture device can store audio information. The audio information may capture sounds associated with the scene that has been captured, which occur at the time of capture. In addition, or alternatively, the audio information may capture the end user's contemporaneous commentary regarding the scene; [0038], one or more image capture devices 104 can produce other kinds of media items, such as video items; [0039], The system 102 encompasses two main components: a knowledge acquisition component 106 and a narrative creation engine 108. The knowledge acquisition component 106 generates a knowledgebase for storage in a data store 110. The knowledgebase provides a repository of information extracted from existing image-annotated narratives obtained from one or more knowledge sources 112. The narrative creation engine 108 receives one or more input images from the end user. The input images describe the end user's own travel experience with respect to one or more locations. The narrative creation engine 108 then leverages the information in the knowledgebase to construct an album narrative. The album narrative provides a cohesive account of the user's travel experience, associated with the set of input images; [0047], the knowledge acquisition component 106 can mine information provided by one or more secondary knowledge sources. Each such secondary knowledge source provides background information regarding topics presented in the above-described type of primary knowledge source. For instance, in addition to mining a primary knowledge regarding the Statue of Liberty from a travel blog, the knowledge acquisition component 106 can extract background information regarding the Statue of Liberty from an online encyclopedia, such as Wikipedia; [0052], the album attribute information can describe, for each image: the location associated with the image, the time-of-capture associated with the image (which reflects the time at which the image was captured), the objects (including landmarks) depicted in the image, the environmental conditions exhibited in the image, the relationships among any people (if any) depicted in the image, the emotions exhibited by the people in the image, and so on; [0055], A narrative creation component 126 constructs a cohesive album narrative based on at least the preliminary narrative information. Subsection A.3 will describe three different techniques for performing this task. As a preview of that subsection, one technique uses a language generation component to generate the album narrative. The language generation component can uses a machine-learned statistical model (e.g., an n-gram model) to perform this task; [0060], FIG. 3 shows an excerpt of an annotated album 302 produced by the system 102 of FIG. 1; [0101], the secondary attribute extraction component 904 can automatically determine the relationship of the people in the input images (see also [0102-104]); [0114], The knowledge lookup component 122 can use the RNN to translate album attribute information associated with each input image into a synthetic textual passage. A training system trains the RNN model based on actual textual passages in travel blogs or the like; [0123], the preliminary narrative information may reflect synthetic textual passages generated by an RNN model or some other machine-learned statistical model; [0124], The language generation component 1004 then commences to generate the words of a textual passage, where that passage can include one or more sentence; [0125], the statistical language model 1006 conditions its output results based on the full wealth of descriptive content contained in the preliminary narrative information; [0131], the style transformation component 1012 can perform the above-described task using an RNN model 1014. More particularly, the RNN model 1014 can correspond to an encoder-decoder type of RNN model which maps the input sentence into a vector, and then maps the vector into the transformed sentence; [0132], the statistical language model 1006 is trained to predict each word w.sub.z in a textual passage, as well as to form a textual passage that reflects a desired style; )
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated generates individual narratives for the individual adventures from the content domains using generative artificial intelligence as suggested in Sahay into Subramanian. Doing so would be desirable because Technology currently allows users to generate and store a large number of digital media items. While on a vacation, for instance, a user may use his or her digital camera, smartphone or wearable computing device to produce dozens of digital photographs that describe his or her travel experience (see Kasina [0001]). A user who captures a large number of digital photographs is faced with the subsequent task of organizing and managing those digital photographs. In traditional practice, a user may perform this task by manually organizing the digital photographs into meaningful folders. Further, a user may manually annotate individual digital photographs with descriptive labels. But this process is labor intensive and tedious in nature. Many users grudgingly perform this task, if at all (see Kasina [0002]). Failure to properly organize a collection of digital photographs may impede the user's later interaction with (and enjoyment of) the digital photographs. A poorly organized corpus of digital photographs may also prevent the user from quickly and effectively sharing his or her digital photographs with others (see Kasina [0003]). The computer-implemented technique provides an efficient mechanism for organizing and presenting digital media items. The technique facilitates the ability of the user to later enjoy his or her own media items, and to also share the media items with others in a timely manner. The technique also efficiently consumes computing resources (e.g., processing and memory resources) because the user may forego (or reduce reliance on) an ad hoc effort to organize the media items, thereby eliminating (or reducing) the expenditure of resources associated with this ad hoc effort (see Kasina [0007]). The narrative creation engine then provides a way of reusing the image-annotated narratives to describe the travel experience exhibited by the end user's own set of input images. By virtue of this capability, the system provides a way by which the end user can quickly organize and describe a collection of images. This capability facilitates the user's later interaction with the images, and allows the user to quickly share the images with others (see Kasina [0040]).
Regarding claim 11, claim 11 contains substantially similar limitations to those found in claim 1, except for managing, in electronic storage (Subramanian 1-6; [0014], a user on a trip through the Himalaya mountains may, at certain times, take digital photos, videos, and post messages to a blog or social network during the trip; [0016], FIG. 1 is an exemplary diagram of a system for automatically generating an electronic journal, including a user interface and a data manager; [0017], Other data sources operably connected to data manager 101 may include a remote server 105 (for example, a file server, data cloud, database, web-blog, web-service, or the like), a social network 106 (for example, at Facebook, Twitter, Google Buzz, and the like); [0019], data manager 101 may be configured to aggregate recorded data that is collected into a series of events that visually portrays a user's activities along a travel route. In this regard, the received GPS location data may include timestamp data that may be associated with timestamp data from the other collected data (for example, digital pictures, video, text messages, blog posts, and the like) recorded at specific points along a route over a period of time. From this data, data manager 101 may generate a virtual trail of location points with each point being associated with one or more photos, videos, text messages, blog posts, or the like; [0021], the collected data is compiled to generate an electronic journal 201 having a format of a chronological story; a condensed blog 208 may also be displayed in connection with map 202; [0023], an event 204 may be determined by comparing collected data with a respective cluster of data having similar features; one or more photos may be compared to determine whether they are substantially similar using color patterns and/or color comparisons. Similar photos may then be included as part of an event 204; [0024], System 100 may also be configured to analyze GPS information to determine a mode of transit, and then include that mode of transit in the generation of journal 102, for example, its text and/or its formatting; [0025], Data manager 101 may be further configured to include, for example, in the generation of text, reverse geocodes determined from comparing the GPS track to known geographical locations; [0027], data manager 101 may determine a confidence level that two or more users are on a joint adventure; claim 7, generating a narrative associated with the one or more travel events, the narrative including sequentially displaying at least a portion of the one or more text messages apart from the interactive map; [0032], In one aspect, computer 501 may display a user interface 507 (for example, user interface 108) to be used by a user 508. User interface 507 may be used to upload and/or integrate a variety of recorded data (including, for example, digital photos, videos, GPS tracks, text messages, blog posts, social network posts, check-in applications, and the like). Consequently, claim 11 is rejected for the same reasons.
Regarding claim 2, Subramanian in view of Kasina teaches all the limitations of claim 1, further comprising:
wherein the user authorization includes input via a client computing platform, wherein the input indicates an authorization to obtain all the pieces of information or particular ones of the pieces of information (Subramanian 1-6; [0017], Other data sources operably connected to data manager 101 may include a remote server 105 (for example, a file server, data cloud, database, web-blog, web-service, or the like), a social network 106 (for example, at Facebook, Twitter, Google Buzz, and the like), online picture storage 107 (for example, Picasa, Flickr, or the like), and/or other systems where data has previously been stored and/or uploaded for other purposes; data manager 101 may collect GPS location data recorded by a GPS-enabled data device 103, and further integrate with a social network to collect data that was posted to the social network over a period of time. In one aspect, a user may set parameters at user interface 108 to configure data manager 101 to only collect data over a predetermined time frame (for example, May 17-19), and/or to only collect data that is associated with a particular subject or tag. Once collected, the GPS location data and other data may then be combined by data manager 101 to generate electronic journal 102; [0032], computer 501 may display a user interface 507 (for example, user interface 108) to be used by a user 508. User interface 507 may be used to upload and/or integrate a variety of recorded data (including, for example, digital photos, videos, GPS tracks, text messages, blog posts, social network posts, check-in applications, and the like). In one aspect, a data source selection screen 509 is displayed by user interface 507 and may include a selectable menu for the selection of a data source; [0033], Parameters may be set at user interface 507 for configuring the system on how data is collected and integrated with system 500 (and/or, for example, data manager 101). For example, a user may configure the cloud to automatically receive data, including a predetermined meta-data tag, when posted to a social network or other online image and/or video host; [0042], appropriate efforts can be taken to protect a user's privacy and other rights. For example, collection and use of location data may be on an opt-in basis so that data is not collected at all unless the user has granted permission, with the location data stored and handled in a secure manner. When collected, the location and other data can be used according to user preferences and/or permissions. For example, sharing of the location data and information derived from the location data (for example, the storyline and/or journal created by the subject technology) may be controlled by the user)
Regarding claim 12, claim 12 contains substantially similar limitations to those found in claim 2. Consequently, claim 12 is rejected for the same reasons.
Regarding claim 3, Subramanian in view of Kasina teaches all the limitations of claim 2, further comprising:
wherein the client computing platform is associated with the user, or is associated with and located at the venue (Subramanian 1-6; [0017], Other data sources operably connected to data manager 101 may include a remote server 105 (for example, a file server, data cloud, database, web-blog, web-service, or the like), a social network 106 (for example, at Facebook, Twitter, Google Buzz, and the like), online picture storage 107 (for example, Picasa, Flickr, or the like), and/or other systems where data has previously been stored and/or uploaded for other purposes; [0031], FIG. 5 is an exemplary diagram of a system 500 for automatically generating an electronic journal, including a user interface for uploading a variety of data, according to one aspect of the subject technology. System 500 may be one implementation of the components described with respect to FIG. 1. System 500 may include, for example, a computer 501 that may be connected to one or more local data devices and/or one or more remote data sources via a network 502, such as the Internet; [0032], computer 501 may display a user interface 507 (for example, user interface 108) to be used by a user 508. User interface 507 may be used to upload and/or integrate a variety of recorded data (including, for example, digital photos, videos, GPS tracks, text messages, blog posts, social network posts, check-in applications, and the like). In one aspect, a data source selection screen 509 is displayed by user interface 507 and may include a selectable menu for the selection of a data source; [0033], Parameters may be set at user interface 507 for configuring the system on how data is collected and integrated with system 500 (and/or, for example, data manager 101). For example, a user may configure the cloud to automatically receive data, including a predetermined meta-data tag, when posted to a social network or other online image and/or video host; [0042], appropriate efforts can be taken to protect a user's privacy and other rights. For example, collection and use of location data may be on an opt-in basis so that data is not collected at all unless the user has granted permission, with the location data stored and handled in a secure manner. When collected, the location and other data can be used according to user preferences and/or permissions. For example, sharing of the location data and information derived from the location data (for example, the storyline and/or journal created by the subject technology) may be controlled by the user)
Regarding claim 13, claim 13 contains substantially similar limitations to those found in claim 3. Consequently, claim 13 is rejected for the same reasons.
Regarding claim 4, Subramanian in view of Kasina teaches all the limitations of claim 1, further comprising:
wherein the user authorization includes: recognition device information for recognition devices, recognizable features, or identification of the one or more companions (Subramanian 1-6; [0017], Other data sources operably connected to data manager 101 may include a remote server 105 (for example, a file server, data cloud, database, web-blog, web-service, or the like), a social network 106 (for example, at Facebook, Twitter, Google Buzz, and the like), online picture storage 107 (for example, Picasa, Flickr, or the like), and/or other systems where data has previously been stored and/or uploaded for other purposes; data manager 101 may collect GPS location data recorded by a GPS-enabled data device 103, and further integrate with a social network to collect data that was posted to the social network over a period of time. In one aspect, a user may set parameters at user interface 108 to configure data manager 101 to only collect data over a predetermined time frame (for example, May 17-19), and/or to only collect data that is associated with a particular subject or tag. Once collected, the GPS location data and other data may then be combined by data manager 101 to generate electronic journal 102; [0032], User interface 507 may be used to upload and/or integrate a variety of recorded data (including, for example, digital photos, videos, GPS tracks, text messages, blog posts, social network posts, check-in applications, and the like). In one aspect, a data source selection screen 509 is displayed by user interface 507 and may include a selectable menu for the selection of a data source. On making a selection at selection screen 509, computer 501 may be configured to access one or more connected data sources and receive the recorded data. In one aspect, selection screen 509 may be used to download recorded data from, or upload recorded data to, a remote server 510. In one aspect, remote server 510 may store the recorded data on a database 511. In another aspect, user interface 507 may also be configured to connect system 500 (and/or, for example, data manager 101) with systems onto which data has previously been stored and/or uploaded for other purposes (for example, a social network). In some aspects, a connection from computer 501 to remote server 510 may require user 508 to provide authentication credentials to server 510; [0033], Parameters may be set at user interface 507 for configuring the system on how data is collected and integrated with system 500 (and/or, for example, data manager 101). For example, a user may configure the cloud to automatically receive data, including a predetermined meta-data tag, when posted to a social network or other online image and/or video host; [0042], appropriate efforts can be taken to protect a user's privacy and other rights. For example, collection and use of location data may be on an opt-in basis so that data is not collected at all unless the user has granted permission, with the location data stored and handled in a secure manner. When collected, the location and other data can be used according to user preferences and/or permissions. For example, sharing of the location data and information derived from the location data (for example, the storyline and/or journal created by the subject technology) may be controlled by the user)
Regarding claim 14, claim 14 contains substantially similar limitations to those found in claim 4. Consequently, claim 14 is rejected for the same reasons.
Regarding claim 5, Subramanian in view of Kasina teaches all the limitations of claim 1, further comprising:
wherein the narrative includes a long form video, short form video, a collection of video clips and photos, or a story book (Subramanian 1-6; [0014], a user on a trip through the Himalaya mountains may, at certain times, take digital photos, videos, and post messages to a blog or social network during the trip; the data may be automatically assembled into a chronological series of events that visually portrays a user's activities along a travel route, together with text, pictures and video; The virtual travel route may be integrated with the other recorded data (for example, digital photos, video, text messages, and the like) via a user interface to generate a visual representation of the user's experience along the route taken during the trip; [0019], In some aspects, data manager 101 may be configured to aggregate recorded data that is collected into a series of events that visually portrays a user's activities along a travel route; data manager 101 may generate a virtual trail of location points with each point being associated with one or more photos, videos, text messages, blog posts, or the like; [0020], FIG. 2 is an exemplary diagram of an automatically generated electronic publication according to one aspect of the subject technology. In the depicted example, an electronic journal 201 (for example, in an online format) is generated to include an interactive map 202, with a virtual travel route 203 superimposed on interactive map 202. At one or more points along route 203, electronic journal 201 may include a collection of notes, pictures, and or other data arranged as events 204. In one aspect, hovering a pointing device over a representation of an event 204 may cause interactive map 202 to activate and display a dialog 205, including one or more image or video thumbnails 206 and/or text associated with event 204. In one aspect, dialog 205 may include one or more buttons 207 for moving through a series of images or the like within dialog 205. In another aspect, selecting dialog 205 may display a page of details associated with event 205. For example, clicking on dialog 205 with a mouse may cause a webpage to appear that includes all recorded data associated with event 204 in a blog format; [0021], electronic journal 201 may include multiple components, such as a map perspective 202, event dialogs 205 (including for example, a video stream, text, and/or one or more pictures arranged as a slide show), and/or a blog; [0026], electronic journal 201 may include a book format, including a map overview on a first page, and an event 204, or a day of activities, represented by each subsequent page; see also [0024], [0030).
Regarding claim 15, claim 15 contains substantially similar limitations to those found in claim 5. Consequently, claim 15 is rejected for the same reasons.
Regarding claim 6, Subramanian in view of Kasina teaches all the limitations of claim 4, further comprising:
wherein the user authorization includes the recognition device information for the recognition devices, and wherein individual ones of the pieces of information are associated with one or more timestamps, wherein the content generation model identifies the individual adventures of the individual users based on the one or more timestamps, image recognition, and/or location information based on the recognition devices of the users (Subramanian 1-6; [0014], the data may be automatically assembled into a chronological series of events that visually portrays a user's activities along a travel route, together with text, pictures and video; [0021], the collected data is compiled to generate an electronic journal 201 having a format of a chronological story, and the chronological story displayed as part of, or in connection with, an interactive map 202; [0022], the system may use face recognition and/or location recognition software and/or hardware to determine one or more subjects of stored photos and/or video data. In one example, a photo (for example, a digital picture) of a known location may be processed by location recognition software to generate coordinates of the known location; [0023-0024], an event 204 may be determined by one or more data having a similar meta-data (for example, timestamps within a certain delta of each other, captured substantially at the same location, or the like); [0027], an initial confidence level may be determined that both users were on a joint adventure. In one aspect, the confidence level may be increased as more common data points and times become available. In another aspect, the system may also use a text classifying system (for example, similar to that used to detect spam) and/or image recognition software to determine similarity or non-similarity between text and/or image data generated by two or more users to determine a higher or lower confidence level; [0030], In step 404, image data is extracted from the one or more digital pictures. The image data may include one or more timestamps, each corresponding to a respective picture. In step 405, the image data is correlated with the travel route and the travel period to generate one or more travel events occurring during the travel period. In one aspect, this may be done by matching a timestamp associated with a digital picture to a timestamp associated with a GPS location data point. In another aspect, this may be done by determining that the timestamps of a plurality of images fall within substantially the same time period, and then matching the time period with one or more GPS location data points; [0032], User interface 507 may be used to upload and/or integrate a variety of recorded data (including, for example, digital photos, videos, GPS tracks, text messages, blog posts, social network posts, check-in applications, and the like). In one aspect, a data source selection screen 509 is displayed by user interface 507 and may include a selectable menu for the selection of a data source. On making a selection at selection screen 509, computer 501 may be configured to access one or more connected data sources and receive the recorded data. In one aspect, selection screen 509 may be used to download recorded data from, or upload recorded data to, a remote server 510. In one aspect, remote server 510 may store the recorded data on a database 511. In another aspect, user interface 507 may also be configured to connect system 500 (and/or, for example, data manager 101) with systems onto which data has previously been stored and/or uploaded for other purposes (for example, a social network). In some aspects, a connection from computer 501 to remote server 510 may require user 508 to provide authentication credentials to server 510; see also [0019-0020])
Regarding claim 16, claim 16 contains substantially similar limitations to those found in claim 6. Consequently, claim 16 is rejected for the same reasons.
Regarding claim 8, Subramanian in view of Kasina teaches all the limitations of claim 1, further comprising:
wherein the pieces of information include one or more of purchase records, captured images and/or videos, scanned event admissions, reservation records, or itineraries (Subramanian 1-6; [0014], the data may be automatically assembled into a chronological series of events that visually portrays a user's activities along a travel route, together with text, pictures and video; The virtual travel route may be integrated with the other recorded data (for example, digital photos, video, text messages, and the like) via a user interface to generate a visual representation of the user's experience along the route taken during the trip; [0018], each time a message or photo pertaining to mountain climbing is posted to the user's social network page the message or photo may be transmitted to data manger 101; [0019], In some aspects, data manager 101 may be configured to aggregate recorded data that is collected into a series of events that visually portrays a user's activities along a travel route; [0024], If the trip is determined to be by air, train, or boat, system 100 may attempt to access a known network location (for example, a travel service) to match the GPS track to a known flight, train or vessel having the same or substantially similar route, and include information relevant to the detected transportation. For example, if the trip is determined to match a known path of a cruise ship, the name and photo of the cruise ship may be included as part of journal 102; [0021], electronic journal 201 may include multiple components, such as a map perspective 202, event dialogs 205 (including for example, a video stream, text, and/or one or more pictures arranged as a slide show), and/or a blog; [0032], computer 501 may display a user interface 507 (for example, user interface 108) to be used by a user 508. User interface 507 may be used to upload and/or integrate a variety of recorded data (including, for example, digital photos, videos, GPS tracks, text messages, blog posts, social network posts, check-in applications, and the like); see also [0030).
Regarding claim 18, claim 18 contains substantially similar limitations to those found in claim 8. Consequently, claim 18 is rejected for the same reasons.
Regarding claim 10, Subramanian in view of Kasina teaches all the limitations of claim 1, further comprising:
wherein the occurrence type includes an experience type or an interaction type (Subramanian 1-6; [0014], The virtual travel route may be integrated with the other recorded data (for example, digital photos, video, text messages, and the like) via a user interface to generate a visual representation of the user's experience along the route taken during the trip; [0017], data manager 101 may collect GPS location data recorded by a GPS-enabled data device 103, and further integrate with a social network to collect data that was posted to the social network over a period of time. In one aspect, a user may set parameters at user interface 108 to configure data manager 101 to only collect data over a predetermined time frame (for example, May 17-19), and/or to only collect data that is associated with a particular subject or tag. Once collected, the GPS location data and other data may then be combined by data manager 101 to generate electronic journal 102; [0024], If the trip is determined to be by air, train, or boat, system 100 may attempt to access a known network location (for example, a travel service) to match the GPS track to a known flight, train or vessel having the same or substantially similar route, and include information relevant to the detected transportation. For example, if the trip is determined to match a known path of a cruise ship, the name and photo of the cruise ship may be included as part of journal 102; [0027], determine that a first traveling user using a first data source 301 and a second traveling user using a second data source 302 are on a joint adventure based on GPS data 303 collected from the first and second data sources. Data source 301 may determine that the first user travelled from point A to G, passing through points C and D. Likewise, data source 302 may determine that the second user travelled from point A to G, passing through points B, D, E, F, and G; [0018], data manager 101 may be integrated with disparate data sources such that each time data is stored or posted to those sources the data is automatically transmitted to data manager 101 and included in electronic journal 102. For example, if a user has configured data manager 101 to generate an electronic journal of a mountain climbing trip, each time a message or photo pertaining to mountain climbing is posted to the user's social network page the message or photo may be transmitted to data manger 101; [0027], Data manager 101 may enable the collaboration of multiple users to participate in the same electronic journal based on similar collected data. In one aspect, data manager 101 may determine a confidence level that two or more users are on a joint adventure (and/or interacting together) based, in part, on manual association at user interface 108, similar GPS patterns, the number of photos taken at a specific location and/or at a particular time, and/or the like; [0032], computer 501 may display a user interface 507 (for example, user interface 108) to be used by a user 508. User interface 507 may be used to upload and/or integrate a variety of recorded data (including, for example, digital photos, videos, GPS tracks, text messages, blog posts, social network posts, check-in applications, and the like))
Regarding claim 20, claim 20 contains substantially similar limitations to those found in claim 10. Consequently, claim 20 is rejected for the same reasons.
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Subramanian in view of Kasina in further view of Andrew et al. (US 20150118667 A1, published 04/30/2015), hereinafter Andrew.
Regarding claim 7, Subramanian in view of Kasina teaches all the limitations of claim 1, further comprising:
wherein information sources of the one or more information sources include accommodation providers and event providers (Subramanian 1-6; abs. generates an electronic journal of a series of events based on input from data sources; [0017], Other data sources operably connected to data manager 101 may include a remote server 105 (for example, a file server, data cloud, database, web-blog, web-service, or the like), a social network 106 (for example, at Facebook, Twitter, Google Buzz, and the like), online picture storage 107 (for example, Picasa, Flickr, or the like), and/or other systems where data has previously been stored and/or uploaded for other purposes; data manager 101 may collect GPS location data recorded by a GPS-enabled data device 103, and further integrate with a social network to collect data that was posted to the social network over a period of time. In one aspect, a user may set parameters at user interface 108 to configure data manager 101 to only collect data over a predetermined time frame (for example, May 17-19), and/or to only collect data that is associated with a particular subject or tag. Once collected, the GPS location data and other data may then be combined by data manager 101 to generate electronic journal 102; [0024], If the trip is determined to be by air, train, or boat, system 100 may attempt to access a known network location (for example, a travel service) to match the GPS track to a known flight, train or vessel having the same or substantially similar route, and include information relevant to the detected transportation. For example, if the trip is determined to match a known path of a cruise ship, the name and photo of the cruise ship may be included as part of journal 102.; [0027], determine that a first traveling user using a first data source 301 and a second traveling user using a second data source 302 are on a joint adventure based on GPS data 303 collected from the first and second data sources. Data source 301 may determine that the first user travelled from point A to G, passing through points C and D. Likewise, data source 302 may determine that the second user travelled from point A to G, passing through points B, D, E, F, and G; [0018], data manager 101 may be integrated with disparate data sources such that each time data is stored or posted to those sources the data is automatically transmitted to data manager 101 and included in electronic journal 102. For example, if a user has configured data manager 101 to generate an electronic journal of a mountain climbing trip, each time a message or photo pertaining to mountain climbing is posted to the user's social network page the message or photo may be transmitted to data manger 101; [0032], computer 501 may display a user interface 507 (for example, user interface 108) to be used by a user 508. User interface 507 may be used to upload and/or integrate a variety of recorded data (including, for example, digital photos, videos, GPS tracks, text messages, blog posts, social network posts, check-in applications, and the like); [0033], Parameters may be set at user interface 507 for configuring the system on how data is collected and integrated with system 500 (and/or, for example, data manager 101). For example, a user may configure the cloud to automatically receive data, including a predetermined meta-data tag, when posted to a social network or other online image and/or video host)
However Subramanian in view of Kasina fails to expressly disclose wherein information sources of the one or more information sources include retailers, accommodation providers, food and beverage providers, and event providers. In the same field of endeavor, Andrew teaches:
wherein information sources of the one or more information sources include retailers, accommodation providers, food and beverage providers, and event providers (Andrew Figs. 1-9; [0026], A storyline is composed of a time-ordered sequence of contexts that partition a given span of time that are arranged into groups at a plurality of hierarchical levels; [0028], One use of storyline data is to offer a historical perspective to the user, who may peruse the storyline to view his/her previous activities. Another use of storyline data is for further processing into interesting aggregations, e.g., identifying a collection of activities that collectively represent a vacation, identifying a group of slices that represent the user's day at work, identifying a pair of travel slices and a stay slice as a trip to the gym, and the like, in accordance with various embodiments of the invention; [0029], the first slice 261 might be a cab ride from the user's hotel to an airport, the second slice 262 might be time spent at the airport, the third slice 263 might be a flight home, the fourth slice 264 might be time spent getting out of the user's home-town airport, and the fifth slice 265 might be a cab ride from the user's home-town airport to the user's apartment; [0030], the third chapter 26 is a journey home from a hotel, the first chapter 22 might be traveling from home to a ski resort and the second chapter 24 might be ten days of skiing; [0032], the storyline might include a book identified as "vacations" that includes a first set of slices corresponding to a weekend in Vegas in April and a second set of slices corresponding to a hike in Yosemite in August. As another example, the storyline might include a chapter identified as "Saturday shopping" that includes two sets of slices corresponding to retail stores in a mall separated by a brief visit to the user's office for a Saturday meeting; [0036], the context refiner module 120 aggregates slices to define groups at one or more hierarchical levels (e.g., chapters, books, etc.) that correspond to semantically meaningful concepts such as work days, work weeks, vacations, compound activities (e.g., a shopping trip made up of visits to multiple stores and the corresponding travel), and the like; [0037], An example of an application that uses a storyline is a mobile phone application that displays the user's history, showing the user the places the user has stayed and the travel between the stays; [0050], a trip involving a drive to the airport, a flight to another city, and a taxi to a hotel might be separated into three distinct travel slices)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated wherein information sources of the one or more information sources include retailers, accommodation providers, food and beverage providers, and event providers as suggested in Andrew into Subramanian in view of Kasina. Doing so would be desirable because the described embodiments generally pertain to interpreting location data and other data about a person collected from mobile devices and internetworked services (see Andrew [0003]). Having a complete record of when and where the user goes is useful for a variety of applications, including recommendation systems, lifelogging, and goal tracking. However, there are a number of obstacles to building useful applications on top of the kinds of data streams currently available (see Andrew [0005]). People generally think about their lives as a collection of time periods with some semantic meaning attached to each period, with a range of levels of abstraction. Raw location data in the form of latitude/longitude readings has no semantic content, and thus does not naturally mesh with how users perceive the corresponding events (see Andrew [0008]). Embodiments of the invention include a method, a non-transitory computer readable storage medium and a system for automated lifelogging to identify, monitor, and help achieve user goals (see Andrew [0010]). Briefly, a context is a (possibly partial) specification of what a user was doing in the dimensions of time, place, and activity. Contexts may only partially specify what a user is doing, omitting one or more of a user's time, place, or activity. Contexts can vary in their specificity, their semantic content, and their likelihood. A storyline is composed of a time-ordered sequence of contexts that partition a given span of time that are arranged into groups at a plurality of hierarchical levels. A storyline is created through a process of data collection, slicing, labeling, and aggregation. The storyline data is then available to offer a historical perspective of the user. With knowledge of the user and the user's routine, the system is then able to identify goals, monitor progress towards goals, and suggest opportunities to meet goals (see Andrew [0026])
Regarding claim 17, claim 17 contains substantially similar limitations to those found in claim 7. Consequently, claim 17 is rejected for the same reasons.
Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Subramanian in view of Kasina in further view of Sahay et al. (US 20170078621 A1, published 03/16/2017), hereinafter Sahay.
Regarding claim 9, Subramanian in view of Kasina teaches all the limitations of claim 1, further comprising:
wherein effectuating presentation of the narrative includes transmitting (Subramanian 1-6; [0014], the data may be automatically assembled into a chronological series of events that visually portrays a user's activities along a travel route, together with text, pictures and video; [0019], In some aspects, data manager 101 may be configured to aggregate recorded data that is collected into a series of events that visually portrays a user's activities along a travel route; [0020], FIG. 2 is an exemplary diagram of an automatically generated electronic publication according to one aspect of the subject technology. In the depicted example, an electronic journal 201 (for example, in an online format) is generated to include an interactive map 202, with a virtual travel route 203 superimposed on interactive map 202. At one or more points along route 203, electronic journal 201 may include a collection of notes, pictures, and or other data arranged as events 204. In one aspect, hovering a pointing device over a representation of an event 204 may cause interactive map 202 to activate and display a dialog 205, including one or more image or video thumbnails 206 and/or text associated with event 204. In one aspect, dialog 205 may include one or more buttons 207 for moving through a series of images or the like within dialog 205. In another aspect, selecting dialog 205 may display a page of details associated with event 205. For example, clicking on dialog 205 with a mouse may cause a webpage to appear that includes all recorded data associated with event 204 in a blog format; [0021], the collected data is compiled to generate an electronic journal 201 having a format of a chronological story, and the chronological story displayed as part of, or in connection with, an interactive map 202; [0034], FIG. 6 is a diagram illustrating an exemplary server system for automatically generating an electronic journal)
However Subramanian in view of Kasina fails to expressly disclose transmitting the narrative via one or more of e-mail, text messaging, social media platforms, or close range wireless communication. In the same field of endeavor, Sahay teaches:
transmitting the narrative via one or more of e-mail, text messaging, social media platforms, or close range wireless communication (Sahay Figs. 1-6; abs. A mechanism is described for facilitating personal assistance for curation of multimedia and generation of stories at computing devices according to one embodiment. A method of embodiments, as described herein, includes receiving, by one or more capturing/sensing components at a computing device, one or more media items relating to an event, and capturing a theme from the one or more media items, where the theme is captured based on at least one of activities, textual content, and scenes associated with the event. The method may further include forming a plurality of story elements to generate a story relating to the event, where the plurality of story elements are formed based on at least one of one or more characters, the theme associated with the event, and one or more emotions associated with the one or more characters, wherein the story is presented, via one or more display devices, to one or more users having access to the one or more display devices; [0055], once story segmentation engine 211 has selected and/or prepared the various parts of the story, feedback and generation/presentation logic 213 may then be triggered to generate the final story or any number of stories to be presented one or more actors and any other users via one or more personal devices, such as personal device 280. For example, an actor/user, wife/mother, in the family vacation example, may choose to view a story using user interface 283, but may also choose to share the story with friends and family by emailing the story or simply posting it on a social networking website, such as Facebook®; [0056], feedback and generation/presentation logic 213 may be used to form other presentation forms of the story for the user to share with other users, such as a shorter form to be posted on Twitter®, a blog to be posted on a website for general public's consumption, and one or more templates of the story to be posted at a story marketplace website for any number and type of users to download and use for their own stories)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated transmitting the narrative via one or more of e-mail, text messaging, social media platforms, or close range wireless communication as suggested in Sahay into Subramanian in view of Kasina. Doing so would be desirable because with the increase in the use and availability of mobile computers and social networking applications, there has been a corresponding increase in user interest in obtaining, organizing, and sharing of media, such as photos, videos, etc. Although there are software applications claiming to offer solutions for organizing media, these conventional techniques are severely limited in that they require their users to perform manual organization of their media, such as collecting and organizing pictures by themes, events, etc. Thus, such conventional techniques require a great deal of effort on part of the users and are time-consuming, inefficient, and prone to errors (see Sahay [0002]). Embodiments provide for a technique serving as an intelligent and efficient personal assistant to help users with automatic and dynamic curation of multimedia items (also referenced as “media items”, “media assets” or simply “media”) (e.g., photos, live or recorded videos, live or recorded audios, live chatter between users, voice messages, text messages, comments posted on websites by users, feedback received from users, television programs, movies, webpages, online posts, blogs, shows, games, concerts, lectures, etc.) to create stories that are capable of being experienced, shared, and offered (see Sahay [0013]). Previous techniques are manual where the user is required to do all the hard work (see Sahay [0016]). Embodiments provide for a comprehensive approach to automated and dynamic media curation, including the ability to interactively edit such stories, share the stories with other users, publish these stories as templates for free or in a marketplace for monetary gains for others to use and re-use, and/or the like (see Sahay [0017]). The system of Sahay would improve the system of Subramanian by enabling the user to easily share a narrative via a desired sharing mechanism, thereby increasing the usefulness desirability of the system (see Sahay [0055-0056]).
Regarding claim 19, claim 19 contains substantially similar limitations to those found in claim 9. Consequently, claim 19 is rejected for the same reasons.
Response to Arguments
The Examiner acknowledges the Applicant’s amendments to claims 1-20. The corrections to claims 1-3, 5, 11-13, and 15 are approved and the previous objections to these claims are respectfully withdrawn. The corrections to claims 1-20 are approved and the previous rejections of these claims under 35 U.S.C. 112(b) are respectfully withdrawn.
Regarding independent claim 1, the Applicant alleges the rejection of the claims under § 101 constitutes legal error and should be withdrawn at least because the Office Action fails to identify a concept recited (i.e., set forth or described) in the claim and explain why it is an abstract idea. The analysis under Step 2A, Prong One is erroneous because (a) the identified abstract idea is not set forth or described by the claims, and/or (b) the Office Action fails to properly explain why the identified abstract idea is an abstract idea (see remarks p. 12). The Office Action's identified abstract idea as stated fails to account for, and cannot be read to encompass, at least the following claim limitations, each of which was identified by the Office Action as part of the abstract idea on page 6: " determine, based on the pieces of information, aspect values that define the aspects of the transportation and the aspects of the occurrences; and " input the aspect values that define the aspects of the transportation and the aspects of the occurrences to the content generation model so that the content generation model determines the adventure of the user and generates, based on the aspect values, a narrative that features the aspects of the occurrences and one or more aspects of the transportation to represent the adventure of the user. These features were treated by the Office Action as constituting the abstract idea. [Office Action, p. 6]. Yet the identified abstract idea ("analyzing information to generate a narrative") does not describe the substance of these operations. Determining aspect values and inputting those values to the content generation model are not acts of "analyzing" information, nor are they acts of "generating" a narrative. The identified abstract idea contains no language accounting for these operations and cannot be read to encompass them (see remarks p. 13). To the extent the Office Action contends that "analyzing information to generate a narrative" is broad enough to reach these operations, that contention only confirms that the identified abstract idea is impermissibly broad (see remarks p. 14). The concept of "analyzing information to generate a narrative" is not an accurate characterization of what is described by the original and/or amended claims. Stated at that level of abstraction, "analyzing information to generate a narrative" is untethered from the language of the claims and does not capture what the claims "recite" and/or are "directed to. Because the identified concept overgeneralizes, it has not been identified as it is set forth or described by the claims, and the Office Action has not shown that the claims recite an abstract idea (see remarks p. 14). The mental-process grouping is limited to concepts that can be practically performed in the human mind; a limitation that cannot practically be performed in the mind does not fall within the grouping. [MPEP § 2106.04(a)(2) III (mental process grouping)]. The Office Action does not apply this standard. It offers only the conclusory assertion quoted above - that the identified concept is "an evaluation or observation" practically capable of being performed in the human mind with pen and paper - without any explanation of how the identified operations could actually be performed in the mind. The relevant question is whether the claimed steps can practically be performed in the mind, and the Office Action never addresses it (see remarks p. 15). Applicant's asserted concept is a specific technological implementation, not an abstract idea. The claims do not recite a narrative claimed at a level of generality; they recite that the narrative be synthesized by a content generation model that uses generative artificial intelligence, operating on the content of stored content domains and on determined aspect values that define the aspects of the user's transportation and experience occurrences. [Specification as filed, 14-16, 27-28]. These operations are carried out by server(s), electronic storage, and one or more hardware processors executing machine-readable instructions that implement the content generation model (see remarks p. 16). Examiner respectfully disagrees.
As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim. As discussed in the rejection above, the claim is directed to an abstract idea that encompasses mental processes including evaluations or observations that are practically capable of being performed in the human mind with the assistance of pen and paper. The claim places no limits on how the analysis and generation is performed. That is, nothing in the claim element precludes the step from practically being performed in the mind. With respect to applicant’s arguments that the abstract idea is impermissibly broad, examiner notes that per MPEP 2106.04, subsection II.B “Unless it is clear that a claim recites distinct exceptions, such as a law of nature and an abstract idea, care should be taken not to parse the claim into multiple exceptions, particularly in claims involving abstract ideas.” Per the USPTO July 2024 update on patent subject matter eligibility “if possible, the examiner should consider the limitations together as a single abstract idea rather than as a plurality of separate abstract ideas to be analyzed individually.”
Under the broadest reasonable interpretation, the terms of the claim are presumed to have their plain meaning consistent with the specification as it would be interpreted by one of ordinary skill in the art. See Manual of Patent Examining Procedure (MPEP) 2111. Thus, the broadest reasonable interpretation of the steps is that those steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04.
Applicant further alleges the Office Action's Prong Two analysis is deficient at least because 1) as a direct consequence of the Prong One deficiencies addressed above, the Office Action's identification of elements allegedly "beyond" the abstract idea appears arbitrary, and/or 2) even accepting the Office Action identification of additional elements relative to the claim features attributed to the identified concept, the additional elements integrate the alleged abstract idea into a practical application (see remarks p. 17). The Prong Two inquiry is relative: an element is "additional" only if it lies beyond the boundaries of the identified judicial exception. The content generation model illustrates the point: the Office Action treats it both as the actor that performs the abstract idea and as an element "beyond" the abstract idea. Because the boundary between the abstract idea and the additional elements was not, and on this record cannot be, reliably drawn, the Office Action has not performed the relative inquiry Prong Two requires, and its determination that the claims fail to integrate the exception into a practical application cannot be sustained on this basis (see remarks p. 18). Applicant further submits that, even under the Office Action's own framework, the additional elements of amended claim 1 integrate the abstract idea into a practical application and the rejection should be withdrawn (see remarks pp. 18-19). These features (at least as recited in amended claim 1) recite a specific ordered combination of additional elements that, taken together, produce a concrete technical result of a personalized narrative that is synthesized by a content generation model utilizing generative Al, thereby automating the generation of a narrative that incorporates content domain content see remarks p. 19). The integration is achieved at least because a) the additional elements, considered individually and in combination, impose a meaningful limit that confines the claim to a particular implementation rather than the abstract idea itself, b) the specific implementation reflects an improvement to a technical field, and/or c) the additional elements are not mere extra-solution activity, nor do they merely link the alleged abstract idea to a particular technological environment or field of use (see remarks p. 20). The additional elements are not invoked merely to implement the abstract idea on a generic computer. Considered in combination - and in combination with the recited operations - they confine the claim to a particular, ordered manner of generating the narrative (see remarks p. 20). So arranged, the additional elements reflect an improvement to the automated generation of narratives. An improvement need not be to computer functionality; the courts have found that improvements to any other technology or technical field demonstrate integration into a practical application, and this consideration applies regardless of the field of the claimed invention (see remarks p. 20). In Example 48 (Speech Separation), claims 2 and 3 recite using a deep neural network to derive embedding vectors and then generate a new, synthesized speech signal from those vectors. [See July 2024 Subject Matter Eligibility Examples, Example 48 at p. 14]. The Office found these claims eligible because the ordered combination of steps reflected the specific improvement described in the specification: separating speech from different speakers without first needing to know how many speakers there are or training the network on their voices (see remarks p. 21). The present claims are like the eligible claims in Example 48, not like the ineligible claim in Example 49: they do not merely name a "content generation mode" and ask it to generate a narrative in the abstract. The claims recite the specific, ordered steps by which the model does so (see remarks pp. 21-22). The Additional Elements Are Not Mere Extra-Solution Activity or a Generic Linking to a Technological Environment (see remarks p. 22). The recited authorization and obtaining of information are not mere data gathering appended to the idea; the obtained information is structured into aspect values that define the aspects of the transportation and the experience occurrences and that direct the content generation model's synthesis of the narrative from the content- domain content. Nor do the recited elements merely link the idea to a technological environment; they specify a particular manner of generating the narrative - from stored content-domain content and structured aspect values, by a content generation model using generative artificial intelligence. The additional elements are therefore neither insignificant extra-solution activity nor a mere linking of the alleged abstract idea to a particular technological environment or field of use (see remarks p. 22).
Regarding additional elements, such as the content generation model, these limitations were analyzed in Step 2A Prong 2 to determine whether they recited additional elements that integrate the exception into a practical application and Step 2B to determine whether they recited additional elements that amount to an inventive concept (aka “significantly more”) than the recited judicial exception. The additional elements amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use, insignificant extra-solution activity, and well-understood, routine, conventional activity. As discussed above, when viewed in combination, the additional elements in the claim do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO).
One way to determine integration into a practical application is when the claimed invention improves the functioning of a computer or improves another technology or technical field. To evaluate an improvement to a computer or technical field, the specification must set forth an improvement in technology and the claim itself must reflect the disclosed improvement. See MPEP 2106.04(d)(1) and 2106.05(a). The consideration of whether the claim as a whole includes an improvement to a computer or to a technological field requires an evaluation of the specification and the claim to ensure that a technical explanation of the asserted improvement is present in the specification, and that the claim reflects the asserted improvement.
While the disclosure states that “As individuals plan and embark on adventures, the individuals may participate in multiple occurrences that involve one or more content domains. Such individuals may manually generate content to memorialize their adventures as keepsakes or to share. However, uniquely incorporating the one or more content domains in the content may be tedious and restricted,” there is no improvement to the functioning of a computer nor to any other technology. At best, the claimed combination amounts to an improvement to the abstract idea of analyzing information to generate a narrative rather than to any technology. See MPEP 2106.05(a).
With respect to example 48, claim 1 of example 48 was found ineligible because the claim does not put any limits on how the mixed speech signal is received, how the temporal features and the spectrogram of the, how the mixed speech signal are obtained, or include any details about the DNN or how it operates. Similar to the limitation “using generative artificial intelligence” in instant claim 1, the DNN of example 48 is used to generally apply the abstract idea without placing any limitation on how the DNN operates. The recited generic DNN merely adds a generic computer component to perform the method and therefore fails to provide an improvement to the technology or technical field
Applicant further alleges that the additional elements of amended claim 1, considered as an ordered combination, provide significantly more than the abstract idea and constitute an inventive concept sufficient to confer patent eligibility (pp. remarks 22-23). The ordered combination of the electronic storage of the content domains and the content generation model, the authorized obtaining and structuring of information into aspect values, and the presentation of the narrative is not a conventional or well- understood arrangement of computer components. The Office Action provides no evidence that, as of the effective filing date, the electronic storage of the content domains and the content generation model, the authorized obtaining and structuring of information into aspect values, and the presentation of the narrative were routinely configured to perform this specific ordered sequence: obtaining, under user authorization and from designated information sources, pieces of information; structuring those pieces into aspect values defining the aspects of the transportation and the experience occurrences; inputting the aspect values to the content generation model to synthesize, using generative artificial intelligence and from the content of the stored content domains, a narrative incorporating that content-domain content; and presenting the narrative to the user (ese remarks p. 23). The Office Action's finding that the additional elements are well-understood, routine, and conventional rests solely on the assertion that they amount to "receiving or transmitting data over a network" [Office Action, pp. 7-8]; that unsupported assertion does not satisfy the evidentiary standard Berkheimer requires to establish that the claimed ordered combination was well-understood, routine, and conventional at the time of filing (see remarks pp. 23-24). Examiner respectfully disagrees.
As discussed above the additional elements individually or in combination with the judicial exception do not provide an inventive concept; so, the claim as a whole does not amount to significantly more than the abstract idea. (Step 2B: NO). The additional limitations amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use, insignificant extra-solution activity, and well-understood, routine, conventional activity. As discussed above, the claim’s recitations of system components amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. As further discussed above, the recitations of receiving user authorization to obtain, from information sources, pieces of information and effectuating a presentation are recited at a high level of generality. These elements amount to receiving or transmitting data over a network and are well understood, routine, conventional activity. See MPEP 2106.05(d), subsection II. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, and therefore do not provide an inventive concept. The claim is not eligible
The Applicant further alleges that Subramanian as described in the previous Office action, does not explicitly teach electronic storage that stores (a) content domains and (b) a content generation model, wherein the content domains include content for subjects of storylines, affiliations between the subjects, descriptions of settings, and anecdotes of the storylines, wherein the content generation model (i) analyzes information to identify individual adventures of individual users, and (ii) generates individual narratives for the individual adventures from the content of the content domains using generative artificial intelligence; one or more processors configured by machine- readable instructions to: obtain, from the content generation model, the narrative, as has been amended to the claim. Examiner has therefore rejected independent claim 1 under 35 U.S.C § 103 as unpatentable over Subramanian in view of Kasina.
Specifically, applicant alleges Subramanian fails to disclose generating narrative content (see remarks p. 26). Examiner respectfully disagrees. As discussed in the rejection above, Subramanian discloses the collected data is compiled to generate an electronic journal 201 having a format of a chronological story, and the chronological story displayed as part of, or in connection with, an interactive map 202; condensed blog 208 may be organized chronologically by event 204 and displayed on a side and apart from map 202, and such that the contents of events 204 are sequentially listed to depict a storyline associated with virtual travel route 203 (see Subramanian [0021] and rejection of claim 1 above). Examiner notes the claims place no limitations on what the narrative must comprise. See also attached NPL dictionary entry for narrative indicating that a narrative is a story, an account, a series of events. Examiner also notes that originally filed claim 5 indicates narrative content includes video, a slideshow of photos, a collection of video clips and photos, a story book, or a photo book. Thus, Subramanian’s disclosure of a narrative story, account, and series of events that include video, photos, and text (Subramanian 1-6; [0014], [0019-0021], [0024], [0030]) is considered within the broadest reasonable interpretation of the claimed limitations.
Applicant further alleges Subramanian fails to disclose storing a content generation model. Subramanian’s specification does not use the word model. Subramanian only discloses storing executable program code and a database of reference facts, and never a stored content generation model (see remarks p. 26). Examiner respectfully disagrees. As discussed in the rejection above, Subramanian discloses FIG. 1 is an exemplary diagram of a system stored on a server for automatically generating an electronic journal (see Subramanian [0016] and rejection of claim 1 above). Data manager 101 may be configured to aggregate recorded data that is collected into a series of events that visually portrays a user's activities along a travel route (Subramanian [0019]). With respect to applicant’s assertion that the data manager model carries out fixed rule based steps (see remarks p. 26), Examiner notes the claims place no limitations on what the model must comprise. See also attached NPL dictionary entry for model indicating that a model is a miniature representation, a pattern, a system of postulates, data, and inferences, a simulation, an example for imitation or emulation, or a design. Thus, Subramanian’s disclosure of a model that analyzes information and generates narratives (Subramanian 1-6; [0014], [0019-0021], [0024], [0030]) is considered within the broadest reasonable interpretation of the claimed limitations.
Similar arguments have been presented for claim 11 and thus, Applicant’s arguments are not persuasive for the same reasons.
Applicant states that the dependent claims recite all the limitations of the independent claims, and thus, are allowable in view of the remarks set forth regarding the independent claims. However, as discussed above, Subramanian in view of Kasina is considered to teach the independent claims, and consequently, the dependent claims are rejected.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Yao (US 20200089810 A1) see Figs. 1-8 and [0025-0028].
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN T REPSHER III whose telephone number is (571)272-7487. The examiner can normally be reached Monday - Friday, 8AM-5PM EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer Welch can be reached at (571) 272-7212. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/JOHN T REPSHER III/ Primary Examiner, Art Unit 2143
Prosecution Insights