DETAILED ACTION
Status of Claims
This communication is the final action on the merits in response to the amendments and arguments filed on September 22, 2025. Claims 1, 12, 19, and 21 were amended. Claims 1-6, 8-17, and 19-22 are currently pending and have been examined.
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 1-6, 8-17, and 19-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-6, 8-11, and 22 are directed to a machine. Claims 12-17 are directed to a process. Claims 19-21 are directed to an article of manufacture. As such, each claim is directed to a statutory category of invention.
Step 2A Prong 1
The examiner has identified independent Claim 1 as the claim that represents the claimed invention for analysis and is similar to independent Claims 12 and 19.
Independent Claim 1 recites the following abstract ideas: “operations, comprising: receiving social media data associated with a user identity from social media operator entity associated with a social media operator entity; creating, based on the social media data and a learning model representative of a collection of rules, an attributable identity token representing experience data representative of experiences associated with the user identity and location data representative of locations associated with the experiences; generating an experience token based on the experience data; providing, based on the attributable identity token and the experience token, a recommendation to a user associated with the user identity to interact with an attraction and an object at an event by providing the user with directions to a location of the attraction and a location of the object, wherein the recommendation is based on a first wait time of the attraction relative to a second wait time associated with a second attraction, and wherein the recommendation indicates to the user that the user should visit the attraction and then visit the second attraction based on a first popularity of the attraction, a second popularity of the second attraction, a first historical importance of the attraction, and a second historical importance of the second attraction, and wherein the recommendation includes a discounted ticket for visiting the attraction; distributing the attributable identity token to social media accounts associated with a group of user identities comprising the user identity, wherein the group of user identities is associated with the social media operator entity; based on the distributing, performing an emoticon analysis that includes a determination that a first emoticon indicates a positive reaction by a second user identity included in the group of user identities to the experience data; and based on the positive reaction, facilitating a payment to an event entity associated with the experience token.”
The limitations, as drafted, are a process that, under its broadest reasonable interpretation, relates to managing relationships or interactions between people including social activities (i.e., operations, comprising: receiving social media data associated with a user identity from a social media operator entity; creating, based on the social media data and a learning model representative of a collection of rules, an attributable identity token representing experience data representative of experiences associated with the user identity and location data representative of locations associated with the experiences; generating an experience token based on the experience data; providing, based on the attributable identity token and the experience token, a recommendation to a user associated with the user identity to interact with an attraction and an object at an event by providing the user with directions to a location of the attraction and a location of the object, wherein the recommendation is based on a first wait time of the attraction relative to a second wait time associated with a second attraction, and wherein the recommendation indicates to the user that the user should visit the attraction and then visit the second attraction based on a first popularity of the attraction, a second popularity of the second attraction, a first historical importance of the attraction, and a second historical importance of the second attraction, and wherein the recommendation includes a discounted ticket for visiting the attraction; distributing the attributable identity token to social media accounts associated with a group of user identities comprising the user identity, wherein the group of user identities is associated with the social media operator entity; based on the distributing, performing an emoticon analysis that includes a determination that a first emoticon indicates a positive reaction by a second user identity included in the group of user identities to the experience data; and based on the positive reaction, facilitating a payment to an event entity associated with the experience token), but for the recitation of generic computer components (i.e., A system comprising a processor, a memory that stores instructions, and equipment). If a claim limitation, under its broadest reasonable interpretation, relates to managing relationships or interactions between people including social activities, but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas.
Accordingly, the claim recites an abstract idea.
Step 2A Prong 2
This judicial exception is not integrated into a practical application. Limitations that are not indicative of integration into a practical application include: (1) Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f)), (2) Adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)), (3) Generally linking the use of the judicial exception to a particular technological environment or field of use (MPEP 2106.05(h)). In particular, the claim recites the additional elements of a system comprising a processor, a memory that stores instructions, and equipment (in addition to the device of Claim 12 and the non-transitory CRM of Claim 19). The computer hardware is recited at a high level of generality (i.e., generic computers receiving, generating, and outputting data) such that it amounts to no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application, since they do not involve improvements to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)), they do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), they do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and they do not apply or use the abstract idea in some other meaningful way beyond generally linking its use to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e)). Therefore, the claim is directed to an abstract idea without a practical application.
Step 2B
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. The additional elements of using computer hardware (a system comprising a processor, a memory that stores instructions, and equipment (in addition to the device of Claim 12 and the non-transitory CRM of Claim 19)) amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Therefore, the claim is not patent-eligible.
Dependent claim 21 recites “video data, photographic data, audio data,” which are described in paragraph [0040] of the specification. The additional elements are generic technology used to implement the abstract idea, and they do not integrate the abstract idea into a practical application, nor are they sufficient to amount to significantly more than the abstract idea when considered both individually and as an ordered combination.
Dependent claims 2-6, 8-11, 13-17, 20, and 22 do not include any additional elements beyond those identified above. They further define the abstract idea that is present in their respective independent claims and hence are abstract for at least the reasons presented above. As such, they do not integrate the abstract idea into a practical application, nor are they sufficient to amount to significantly more than the abstract idea when considered both individually and as an ordered combination.
Therefore, dependent claims 2-6, 8-11, 13-17, and 20-22 are directed to an abstract idea, and do not include additional elements that integrate the abstract idea into a practical application, or that are sufficient to amount to significantly more than the abstract idea. Thus, the aforementioned claims are not patent-eligible.
Claim Rejections - 35 USC § 103
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-2, 5, 8-12, 15-16, 19, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Afshar (US-11979365) in view of Nenkova et al. (US-20220027858), Brannan et al. (US-12373892), and Morris (US-20170186029).
Claim 1 (and Similarly Claims 12 and 19)
Afshar teaches the following limitations:
A system comprising: a processor; and a memory that stores instructions that, when executed by the processor, facilitates performance of operations, comprising: receiving social media data associated with a user identity from social media operator entity equipment associated with a social media operator entity (Col. 3 Lines 13-19 the present technology provides for generating a life story for a user that can be accessed through a content sharing platform, such as a social networking system. For example, the life story for the user can be created based on content items that are shared by the user or are otherwise associated with the user, such as content items in which the user is tagged or from which the user is otherwise recognized; Col. 12 Lines 61-67 The social networking system 630 may be administered, managed, or controlled by an operator. The operator of the social networking system 630 may be a human being, an automated application, or a series of applications for managing content, regulating policies, and collecting usage metrics within the social networking system 630. Any type of operator may be used);
creating, based on the social media data and a learning model representative of a collection of rules, an attributable identity token representing experience data representative of experiences associated with the user identity and location data representative of locations associated with the experiences (Col. 3 Lines 15-30 the life story for the user can be created based on content items that are shared by the user or are otherwise associated with the user, such as content items in which the user is tagged or from which the user is otherwise recognized. Content items to be included in the life story can be curated manually or automatically. Under such approaches, content items that reference important moments in the user's life can be selected for inclusion in the life story. Such content items can reference major life events (e.g., weddings, anniversaries, birthdays, births, etc.), friendships (e.g., formation of a friendship, a friendship anniversary, etc.), life stages (e.g., school years, college years, etc.), and significant events (e.g., birth of a child, a new year's eve celebration, holidays, cultural events, starting a new company, moving to a new city, etc.), to name some examples; Col. 6 Lines 13-17 the generating module 104 can automatically identify content items to be included in a life story for a user without requiring manual selection of content items. The generating module 104 can automatically identify content items based on a number of techniques; Col. 7 Lines 9-23 Other approaches for determining content items to include in a life story are contemplated. For example, in some embodiments, the generating module 104 can train and apply a machine learning model that determines whether to include a content item in a life story based on training data associated with content items. Such training data can include an author of the content item, text associated with the content item, media associated with the content item, and user interactions with the content item (e.g., reactions, comments, reshares, etc.), to name some examples. Such training data also can include labels indicating whether a content item should be included in a life story. In an evaluation phase, the trained machine learning model can output a likelihood that a content item should be included in a life story; Col. 7 Lines 39-43 The generating module 104 can optionally associate content items included in a life story with graphical overlays. A graphical overlay may include text and/or media that describes a context associated with a single content item or a group of related content items; Col. 7 Line 59-Col. 8 Line 3 When determining a graphical overlay for a content item, the generating module 104 can determine a context associated with the content item based on various signals. For example, in some embodiments, the generating module 104 can determine a context associated with the content item based on a geographic location and timestamp associated with the content item. An event calendar that identifies various events (e.g., cultural events, religious events, holidays, etc.) that occur throughout the world can be used to identify an event that corresponds to the geographic location and timestamp associated with the content item);
generating an experience token based on the experience data (Col. 3 Lines 15-30 the life story for the user can be created based on content items that are shared by the user or are otherwise associated with the user, such as content items in which the user is tagged or from which the user is otherwise recognized. Content items to be included in the life story can be curated manually or automatically. Under such approaches, content items that reference important moments in the user's life can be selected for inclusion in the life story. Such content items can reference major life events (e.g., weddings, anniversaries, birthdays, births, etc.), friendships (e.g., formation of a friendship, a friendship anniversary, etc.), life stages (e.g., school years, college years, etc.), and significant events (e.g., birth of a child, a new year's eve celebration, holidays, cultural events, starting a new company, moving to a new city, etc.), to name some examples);
distributing the attributable identity token to social media accounts associated with a group of user identities comprising the user identity, wherein the group of user identities is associated with the social media operator entity (Col. 3 Lines 30-39 When the life story is accessed, each content item included in the life story can be provided for display in chronological order. Thus, the life story can provide a digital biography of the user as told through content items associated with the user. Viewers can access the life story to learn more about the user, for example, based on the chronological presentation of the content items. In some instances, the viewers can engage with the content items through social interactions (e.g., reactions, comments, etc.); Col. 8 Line 56-Col. 9 Line 2 Once a life story for a user is generated, the life story can be made accessible to other users of the content sharing system. For example, an option 304 in an example interface 302 can be provided for presentation through a display of a computing device of a viewer, as illustrated in FIG. 3A. The option 304 can be selected to access the life story. In another example, a profile interface 308 associated with the user can be provided for presentation through the display of the computing device of the viewer, as illustrated in FIG. 3B. The life story may be accessed through an option 310 provided in the profile interface 308 associated with the user. When the life story is accessed, the provisioning module 106 can provide the life story for presentation on a display screen);
based on the distributing, performing an emoticon analysis that includes a determination that a first emoticon indicates a positive reaction by a second user identity included in the group of user identities to the experience data (Col. 6 Lines 51-60 users of the content sharing system can engage with the content item using reactions. As examples, the reactions can include a like option, a heart option, a care option, a funny option, a surprise option, a sad option, and an angry option, to name some examples. In some embodiments, a content item that is associated with a threshold amount (e.g., count, percentage, etc.) of positive reactions (e.g., like reactions, heart reactions, funny reactions, care reactions) can be identified as having a positive sentiment); and
However, Afshar does not explicitly teach the following limitations:
providing, based on the attributable identity token and the experience token, a recommendation to a user associated with the user identity to interact with an attraction and an object at an event by providing the user with directions to a location of the attraction and a location of the object, wherein the recommendation is based on a first wait time of the attraction relative to a second wait time associated with a second attraction, and wherein the recommendation indicates to the user that the user should visit the attraction and then visit the second attraction based on a first popularity of the attraction, a second popularity of the second attraction, a first historical importance of the attraction, and a second historical importance of the second attraction, and wherein the recommendation includes a discounted ticket for visiting the attraction;
based on the positive reaction, facilitating a payment to an event entity associated with the experience token.
Nenkova, in the same field of endeavor, teaches the following limitations:
providing, based on the attributable identity token and the experience token, a recommendation to a user associated with the user identity to interact with an attraction and an object at an event by providing the user with directions to a location of the attraction and a location of the object, wherein the recommendation is based on a first wait time of the attraction relative to a second wait time associated with a second attraction, and wherein the recommendation indicates to the user that the user should visit the attraction and then visit the second attraction based on a first popularity of the attraction, a second popularity of the second attraction, a first historical importance of the attraction, and a second historical importance of the second attraction ([0015] one or more processors may receive user specific data and location data. In some embodiments, the user specific data may include data about the user and the user's preferences regarding the location. In some embodiments, the location data may include current and historical data about the location. As an example, the location data may be data about a theme park, and the user specific data may be data about a visitor to the theme park and her preferences for her visit; [0017] The user specific data may also include geospatial information such as the current location of the user; [0029] the user specific data may include data gathered from one or more social media accounts associated with the user. Social media accounts may include methods of sharing information by the Internet with one or more other users via social media platforms. Social media data may be gathered from posts on social media platforms, comments or responses (such as likes) to posts on social media, or other means of conveying information on social media such as interests expressed, direct messages, inquiries made, answers provided, videos or links posted, individuals or groups followed, etc.; [0030] For example, a picture of someone skydiving shared on social media may indicate that the user has a preference for rides of higher ride intensity or may enjoy rides where a rider experiences free fall or lengthy downhill drops on a roller coaster. As another example, the user may have indicated an interest in a particular movie and based on data indicating an interest in the movie, the user may be directed towards a show or a themed ride based on the characters of the movie; [0018] the location data may include historical data or current data about the theme park. For example, location data may include data about attractions at the location (e.g., rides and shows of the theme park), including, a list of available rides, ride locations, real-time attraction status (e.g., is the ride or show open, closed, only operating at half capacity, under maintenance, closed for a short while), attraction popularity scores, real-time length of all lines (for rides, shows, etc.), estimated wait times in real-time, historical wait times for attractions, variations in historical wait times for attractions based on various factors (e.g., historically wait times for shows are greater (and by how much) in the afternoons immediately after lunch, historical wait times for water rides are greater (and by how much) on days above 90 degrees that are not cloudy, historical wait times for one specific ride increase two-fold if another specific ride is closed for maintenance), ride intensity, physical restrictions for the attractions, and a list of popular attractions as rated by guests; [0020] the one or more processors may utilize a recommendation machine learning algorithm to analyze the user specific data and location data. In some embodiments, the recommendation machine learning algorithm may be any machine learning algorithm capable of utilizing the user specific data, location data, real-time user data (described below), and changes to the user specific and location data to provide a recommendation score and ranking for each of one or more locations or items at the location (e.g., park attractions, rides, shows) for the user; [0021] the one or more processors may generate a visit recommendation using the recommendation machine learning algorithm. In some embodiments, the visit recommendation may comprise one or more recommended locations. For example, the visit recommendations may be a list of theme park attractions, including theme park rides and theme park shows, which are recommended for the user based on the user specific data and location data provided; [0022] the one or more processors may arrange, utilizing a scheduling algorithm, the one or more recommended locations of the visit recommendation into a visit schedule. The scheduling algorithm may be any algorithm, including a machine learning algorithm, which is able to arrange, order, or group the one or more recommendations, based on parameters such as optimization of number of locations, minimization of wait times at locations, minimization of time in route to the locations, or minimization of crowding by multiple users at specific locations; [0023] For example, the visit schedule may list the theme park attractions (e.g., theme park rides and theme park shows) in an order to be visited. As another example, the visit schedule may include groups of attractions to be visited at various times of the day. As another example, the visit schedule may include recommended time slots (e.g., from 2 pm to 4 pm) for visiting one or more attractions; [0027] The graphical user interface may display details about the one or more recommended locations which may inform the user about whether the user would like to visit the locations. These details may include wait times at theme park attractions, recommendations or requirements regarding who the attractions are suitable for (e.g., age and height requirements for amusement park rides), reviews of the attractions gathered from historical data from other users (e.g., through a feedback collection system run internally or from external sources such as websites), the location of the attraction (e.g., how far the visitor must walk to get to the attraction), or other information useful to users. The graphical user interface may provide guidance on the best way (e.g., fastest route, shaded route, or ADA accessible route) to get to the location; [0028] For example, a suggested route and alternative suggested routes may be mapped out on a map feature displayed on the graphical user interface), and
This known technique is applicable to the system of Afshar as they both share characteristics and capabilities, namely, they are directed to event-based social media platforms. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Nenkova would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Nenkova to the teachings of Afshar would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., providing a recommendation to a user to visit an attraction and/or event, based on the user’s data, and based on features/attributes of the attraction) into similar systems.
However, Afshar, in combination with Nenkova, does not explicitly teach the following limitations:
wherein the recommendation includes a discounted ticket for visiting the attraction;
based on the positive reaction, facilitating a payment to an event entity associated with the experience token.
Brannan, in the same field of endeavor, teaches the following limitations:
wherein the recommendation includes a discounted ticket for visiting the attraction (Col. 12 Lines 1-8 products may include notifications of nearby events. For example, a user enters, or is within, a geofence defined around the location of an event (e.g., a concert or a food festival), and the product identification message includes a notification to the user regarding the event. The product may further include an offer associated with the event (e.g., a discount on tickets or an offer for a free item if the user attends the event)).
This known technique is applicable to the system of Afshar, in combination with Nenkova, as they both share characteristics and capabilities, namely, they are directed to event-based platforms. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Brannan would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Brannan to the teachings of Afshar, in combination with Nenkova, would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., providing a discounted ticket to visit an event / attraction) into similar systems.
However, Afshar, in combination with Nenkova and Brannan, does not explicitly teach the following limitations:
based on the positive reaction, facilitating a payment to an event entity associated with the experience token.
Morris, in the same field of endeavor, teaches the following limitations:
based on the positive reaction, facilitating a payment to an event entity associated with the experience token ([0024] The bid 135 may also define an action which triggers the advertiser system 104 to pay the social networking system 110, also denoted herein as the “bid goal” of the ad... the bid 135 may be predicated on a specific user interaction (i.e., payment is received by the social networking system 110 whenever a user interacts with the ad in a predefined manner). This user interaction may be... providing positive feedback to a page on the social networking system 110, instructing the social networking system 110 to share the ad 131 or a page with other users who are associated with the user (e.g., share the ad with “friends” of the user), or some other interaction; [0077] The bidding panel 520 displays the bid type of the sponsored post 512. The bid type of the sponsored post 522 is based on page “likes.” Thus, the advertiser system 104 pays the social networking system 110 whenever a user to whom the ad is presented “likes” the page associated with the sponsored post 512. A “like” which triggers advertiser system 104 to pay the social networking system 110 may be initiated by a user pressing the “like page” button 517).
This known technique is applicable to the system of Afshar, in combination with Nenkova and Brannan, as they both share characteristics and capabilities, namely, they are directed to social media platforms. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Morris would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Morris to the teachings of Afshar, in combination with Nenkova and Brannan, would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., a content provider paying for engagement with their content on social media) into similar systems.
Claim 2
Afshar further teaches the following limitations:
wherein the operations further comprise identifying, based on the social media data, a location of the location data and a time corresponding to the location, and determining, based on the location and the time, that the user associated with the user identity attended the event that took place at the location and the time (Col. 7 Line 55-Col. 8 Line 6 a graphical overlay can be generated for a content item that references a major life event. For example, a content item reflecting people getting married can be presented with a “Wedding Day” graphical overlay. Many variations are possible. When determining a graphical overlay for a content item, the generating module 104 can determine a context associated with the content item based on a geographic location and timestamp associated with the content item. An event calendar that identifies various events (e.g., cultural events, religious events, holidays, etc.) that occur throughout the world can be used to identify an event that corresponds to the geographic location and timestamp associated with the content item. In such embodiments, the generating module 104 can associate the content item with a graphical overlay that corresponds to the identified event (e.g., “Merry Christmas”, “Happy Holi”, “Happy Lunar New Year”, etc.)).
Claim 5
Afshar further teaches the following limitations:
wherein the attributable identity token is a tuple of a collection of tuples (Col. 3 Lines 30-37 When the life story is accessed, each content item included in the life story can be provided for display in chronological order. Thus, the life story can provide a digital biography of the user as told through content items associated with the user. Viewers can access the life story to learn more about the user, for example, based on the chronological presentation of the content items).
Claim 8
Afshar further teaches the following limitations:
wherein the experience data comprises content input via social media accounts associated with the user identity, and wherein the operations further comprise distributing the experience token to the social media accounts associated with the group of user identities (Col. 3 Lines 15-30 the life story for the user can be created based on content items that are shared by the user or are otherwise associated with the user, such as content items in which the user is tagged or from which the user is otherwise recognized. Content items to be included in the life story can be curated manually or automatically. Under such approaches, content items that reference important moments in the user's life can be selected for inclusion in the life story. Such content items can reference major life events (e.g., weddings, anniversaries, birthdays, births, etc.), friendships (e.g., formation of a friendship, a friendship anniversary, etc.), life stages (e.g., school years, college years, etc.), and significant events (e.g., birth of a child, a new year's eve celebration, holidays, cultural events, starting a new company, moving to a new city, etc.), to name some examples; Col. 8 Line 56-Col. 9 Line 2 Once a life story for a user is generated, the life story can be made accessible to other users of the content sharing system. For example, an option 304 in an example interface 302 can be provided for presentation through a display of a computing device of a viewer, as illustrated in FIG. 3A. The option 304 can be selected to access the life story. In another example, a profile interface 308 associated with the user can be provided for presentation through the display of the computing device of the viewer, as illustrated in FIG. 3B. The life story may be accessed through an option 310 provided in the profile interface 308 associated with the user. When the life story is accessed, the provisioning module 106 can provide the life story for presentation on a display screen).
Claim 9
Afshar further teaches the following limitations:
wherein the user identity is a first user identity, and wherein the operations further comprise based on the distributing of the experience token, determining that user input, associated with a third user identity that is a member of the group of user identities, has resulted in the experience token being updated (Col. 9 Lines 2-5 FIG. 3C illustrates an example interface 312 that can be provided for presentation through the display of the computing device of the viewer. The interface 312 provides access to the life story; Col. 9 Lines 12-14 Viewers accessing the life story can interact with individual content items based on various options 320 (e.g., react, comment, etc.)).
Claim 10
Afshar further teaches the following limitations:
wherein the user input associated with the third user identity that has resulted in the experience token being updated comprises a comment input with respect to the experience token associated with the third user identity that results in the comment being associated with the experience token (Col. 9 Lines 2-5 FIG. 3C illustrates an example interface 312 that can be provided for presentation through the display of the computing device of the viewer. The interface 312 provides access to the life story; Col. 9 Lines 12-14 Viewers accessing the life story can interact with individual content items based on various options 320 (e.g., react, comment, etc.)).
Claim 11
Afshar further teaches the following limitations:
wherein the user input associated with the third user identity that has resulted in the experience token being updated comprises an emoticon input with respect to the experience token associated with the third user identity that results in the emoticon input being associated with the experience token (FIG. 3C, Options 320 (reactions); Col. 9 Lines 2-5 FIG. 3C illustrates an example interface 312 that can be provided for presentation through the display of the computing device of the viewer. The interface 312 provides access to the life story; Col. 9 Lines 12-14 Viewers accessing the life story can interact with individual content items based on various options 320 (e.g., react, comment, etc.)).
Claim 15
Afshar further teaches the following limitations:
wherein the experience token represents content input via a social media account associated with the user identity describing an experience that occurred at a second attraction associated with the location data (Col. 7 Line 63-Col. 8 Line 3 the generating module 104 can determine a context associated with the content item based on a geographic location and timestamp associated with the content item. An event calendar that identifies various events (e.g., cultural events, religious events, holidays, etc.) that occur throughout the world can be used to identify an event that corresponds to the geographic location and timestamp associated with the content item).
Claim 16
Afshar further teaches the following limitations:
wherein the user identity is a first user identity, and further comprising distributing, by the device, the experience token to social media accounts respectively associated with user identities comprising at least the first user identity and a third user identity (Col. 8 Line 56-Col. 9 Line 2 Once a life story for a user is generated, the life story can be made accessible to other users of the content sharing system. For example, an option 304 in an example interface 302 can be provided for presentation through a display of a computing device of a viewer, as illustrated in FIG. 3A. The option 304 can be selected to access the life story. In another example, a profile interface 308 associated with the user can be provided for presentation through the display of the computing device of the viewer, as illustrated in FIG. 3B. The life story may be accessed through an option 310 provided in the profile interface 308 associated with the user. When the life story is accessed, the provisioning module 106 can provide the life story for presentation on a display screen).
Claim 21
Afshar further teaches the following limitations:
wherein the experience token includes video data, photographic data, audio data, location data, time data and object data (Col. 5 Lines 5-21 a life story can be created based on content items that are accessible through the content sharing system… As examples, such content items can comprise shared posts that include text (or captions) and/or media (e.g., images, videos, audio, etc.), stories (e.g., user-generated media collections), user-specified life events, links to other content (e.g., other posts, stories, websites, etc.), and updates to a user profile or status (e.g., adding a favorite book at a particular time, check-in at a significant location, marking oneself as being safe from a natural disaster or crisis, etc.); Col. 7 Line 39-Col. 8 Line 36 The generating module 104 can optionally associate content items included in a life story with graphical overlays… When determining a graphical overlay for a content item, the generating module 104 can determine a context associated with the content item based on various signals. For example, in some embodiments, the generating module 104 can determine a context associated with the content item based on a geographic location and timestamp associated with the content item. An event calendar that identifies various events (e.g., cultural events, religious events, holidays, etc.) that occur throughout the world can be used to identify an event that corresponds to the geographic location and timestamp associated with the content item… the generating module 104 can determine a context associated with a content item based on check-in information. For example, a user that posted the content item can specify check-in information that identifies an event or point of interest),
Nenkova further teaches the following limitations:
wherein the recommendation indicates to the user that the user should visit the attraction and then visit the second attraction based on a first scenic perspective of the attraction and a second scenic perspective of the second attraction ([0022] the one or more processors may arrange, utilizing a scheduling algorithm, the one or more recommended locations of the visit recommendation into a visit schedule; [0023] For example, the visit schedule may list the theme park attractions (e.g., theme park rides and theme park shows) in an order to be visited; [0024] the one or more processors may revise the visit recommendation or visit schedule using real-time user data; [0025] based on the real-time user data, the visit schedule may be revised to alter the order or timing of a user's visit to specific locations or types of locations (e.g., based on real-time weather data indicating that a thunderstorm will affect the area of the park for one hour, the visit schedule may be revised to switch the recommended order of the locations and attractions on the visit schedule so that an indoor show is scheduled for the time of the thunderstorm, rather than a large rollercoaster); [0041] the missed recommended item feature may assist the user to go to the next recommended item or to another place instead. For example, directions and/or a map showing the locations of the Ferris wheel or other places (food, quiet place to sunbathe, etc.), and routes to them, may be provided to the user).
This known technique is applicable to the system of Afshar as they both share characteristics and capabilities, namely, they are directed to event-based social media platforms. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Nenkova would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Nenkova to the teachings of Afshar would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., providing a recommendation to a user to visit an attraction and/or event, based on features/attributes of the attraction) into similar systems.
Claims 3-4, 6, 13-14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Afshar (US-11979365) in view of Nenkova et al. (US-20220027858), Brannan et al. (US-12373892), and Morris (US-20170186029), and further in view of Brownhill et al. (US-20190139088).
Claim 3
Afshar, in combination with Nenkova, Brannan, and Morris, does not explicitly teach the following limitations:
wherein the location of the location data comprises a coordinate representing a geographic longitude and a geographic latitude associated with the event.
Brownhill, in the same field of endeavor, teaches the following limitations:
wherein the location of the location data comprises a coordinate representing a geographic longitude and a geographic latitude associated with the event ([0009] the event is associated with a particular time and a particular location, and the geo-location information associated with the user indicates that the user is located at the particular location at the particular time; [0068] the contributor invitation module 204 can identify the set of contributors for an event story by identifying a set of users that are attending an event associated with the event story… the contributor invitation module 204 can determine that a user is attending an event based on geo-location information associated with the user and current time information. For instance, if an event is scheduled to take place at a particular location at a particular time, and it is determined that the user is in the particular location at the particular time, a determination can be made that the user is attending the event. User geo-location information can include GPS information from a user's mobile device, geo-fencing information from the user's mobile device, near field communications, low-power Bluetooth beacon communications, or any other indicator and/or source of user location information).
This known technique is applicable to the system of Afshar, in combination with Nenkova, Brannan, and Morris, as they both share characteristics and capabilities, namely, they are directed to the creation of social media event stories from the aggregation of event-related content items. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Brownhill would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Brownhill to the teachings of Afshar, in combination with Nenkova, Brannan, and Morris, would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., location data comprising coordinates representing latitude and longitude associated with an event) into similar systems.
Claim 4
Afshar, in combination with Nenkova, Brannan, and Morris, does not explicitly teach the following limitations:
wherein the location data represents geo-fencing data indicative of boundaries associated with the user identity, and wherein the location of the location data comprises a geo-fence of the geo-fencing data indicative of a boundary associated with the event.
Brownhill, in the same field of endeavor, teaches the following limitations:
wherein the location data represents geo-fencing data indicative of boundaries associated with the user identity, and wherein the location of the location data comprises a geo-fence of the geo-fencing data indicative of a boundary associated with the event ([0009] the event is associated with a particular time and a particular location, and the geo-location information associated with the user indicates that the user is located at the particular location at the particular time; [0068] the contributor invitation module 204 can identify the set of contributors for an event story by identifying a set of users that are attending an event associated with the event story... the contributor invitation module 204 can determine that a user is attending an event based on geo-location information associated with the user and current time information. For instance, if an event is scheduled to take place at a particular location at a particular time, and it is determined that the user is in the particular location at the particular time, a determination can be made that the user is attending the event. User geo-location information can include GPS information from a user's mobile device, geo-fencing information from the user's mobile device, near field communications, low-power Bluetooth beacon communications, or any other indicator and/or source of user location information).
This known technique is applicable to the system of Afshar, in combination with Nenkova, Brannan, and Morris, as they both share characteristics and capabilities, namely, they are directed to the creation of social media event stories from the aggregation of event-related content items. One of ordinary skill in the art, before the effective filing date of the claimed invention, would have recognized that applying the known technique of Brownhill would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Brownhill to the teachings of Afshar, in combination with Nenkova, Brannan, and Morris, would have yielded predictable results because the level of one of ordinary skill in the art would have known to incorporate such features (i.e., location data representing geo-fencing data associated with an event and attendees of an event) into similar systems.
Claim 6
Afshar, in combination with Nenkova, Brannan, and Morris, does not explicitly teach the following limitations:
wherein the operations further comprise clustering the attributable identity token in a cluster of attributable identity tokens based on a time stamp value included in the social media data.