DETAILED ACTION
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 .
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 19 July 2024 is/are being considered by the examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 6-8 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 6, and mutatis mutandis claims 7 and 8, recite the limitation “the classification results” in line 2. There is insufficient antecedent basis for this limitation in the claim.
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.
Claim(s) 1-20 are rejected under 35 U.S.C. §101 because the claimed invention is directed to an abstract idea without significantly more.
To determine subject matter eligibility for each of the recited claims above, we turn to the subject matter eligibility test, also referred to as the Alice/Mayo test, described in MPEP 2106. Regarding step 1 of the subject matter eligibility test, we first determine if the claims are directed to a statutory category. The independent claim(s) 1, and mutatis mutandis claim(s) 14 and 15, recite “classifying chat messages received during a live broadcast of a host using a function of a live commerce tool for the host” As the claims recite a process and a machine, the claim is directed to one of the statutory categories under step 1 of the subject matter eligibility test.
In Step 2A of the test, which is a Two Prong analysis, we then determine if the claim is directed to a judicial exception. For Step 2A, Prong One, we first ask if the claim recites an abstract idea, Law of Nature, or Natural Phenomena. Regarding claim(s) 1, 14, and 15, the limitation of “classifying…” as drafted cover managing personal behavior or relationships or interactions between people, which is a method of organizing human activity, as described in the context of a mental process. More specifically, the claims describe reading a chat and mentally classifying its intent, as part of the managing of commercial interactions and communications between a seller (the host) and potential buyers (the viewers) as part of a presentation (e.g., the live broadcast). Therefore, the claims are directed to mental processes and human activity, and, thus, directed to an abstract idea which is a judicial exception.
In Step 2A, Prong Two of the analysis, we next determine if the claim recites additional elements which integrate the judicial exception into a practical application. The judicial exception recited in claims 1, 14, and 15 is not integrated into a practical application. In particular, claim(s) 1, 14, and 15 recite additional elements of a “executed by a computing device”, and “using a function of a live commerce tool”, as per the independent claims. Regarding “executed by a computer device,” the computer device and all components thereof are general-purpose computer components which are not meaningfully integrated into the practical application of the abstract ideas recited in claim(s) 1, 14, and 15. The computer device is described in the context of a processor performing a generic function in light of instructions stored in the memory. Processor and memory, as integrated in and implemented through the computer device, are recited at a high-level of generality (i.e., as a generic processor of a computer device performing a generic computer function based on instructions stored in a generic memory, the function being classifying chat messages) such that it amounts no more than mere instructions to apply the exception using a generic computing device and/or a generic computer component. Regarding the “using a function of a live commerce tool”, both the “function” and the “live commerce tool” are described at such a high level of abstraction, that each merely provide a technological environment for the abstract idea to be performed. Accordingly, the additional elements fail to integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Regarding Step 2B of the analysis, we next determine if the claim recites additional elements which amount to substantially more than the judicial exception. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional element of using a “processor,” a “memory,” or “computer readable instructions” to perform the classification of chat messages amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using a generic computing device or general purpose computer component cannot provide an inventive concept. (See Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 223, 110 USPQ2d 1976, 1982-84 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Further, “merely identifying a user interface” with relation to determinations which “can be performed in the human mind or using a pencil and paper” has been deemed insufficient to render otherwise abstract claims as non-abstract, where the court further indicated that the resulting device, system and/or method was “still missing” an “improved structure or function.” See Broadband iTV, Inc. v. Amazon.com, Inc., 113 F.4th 1359, 1367-68 (Fed. Cir. 2024). The court has consistently held that “[s]teps that do nothing more than spell out what it means to ‘apply it on a computer’ cannot confer patent-eligibility.” Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1371-72 (Fed.Cir. 2015)(citing Alice, 134 S.Ct. at 2359 (warning against a § 101 analysis that turns on the draftsman's art (citing Parker v. Flook, 437 U.S. 584, 593, 98 S.Ct. 2522, 57 L.Ed.2d 451 (1978))).
Therefore, and in light of the preceding analysis, the claims do not amount to significantly more than the judicial exception. For these reasons, claims 1, 14, and 15 are not patent eligible.
With respect to claim(s) 2 and 16, the claims relate to classifying based on content using a language model. As performed by a person, these steps appear to refer to the mental process of using well known categories for the previously described classification, as performed in a well-known technological environment (e.g., a language model). No additional limitation is present.
With respect to claim(s) 3, the claim relates to generating categories for the classification based on examples, using prompts to a language model. As performed by a person, these steps appear to refer to the mental process of using categories as applied to known examples for the previously described classification, as performed in a well-known technological environment (e.g., a language model). No additional limitation is present.
With respect to claim(s) 4 and 17, the claims relate to generating categories for the classification and presenting the chat messages in a new interface. As performed by a person, these steps appear to refer to the mental and clerical process of determining classifications based on categories and actually presenting the chats in the respective categories. No additional limitation is present.
With respect to claim(s) 5 and 18, the claims relate to analyzing real time messages and presenting analysis results. As performed by a person, these steps appear to refer to the mental and clerical process of performing an analysis on a message (e.g., determining what the underlying meaning of the message is, as done normally in the human mind) and actually presenting the results of that analysis (e.g., writing it down). No additional limitation is present.
With respect to claim(s) 6, the claims relate to the analysis including positive and negative reaction rates. As performed by a person, these steps appear to refer to the mental process of restricting the analysis to a determination of positive or negative sentiment, as well as determining trends of the same (which can be done mentally or mathematically). No additional limitation is present.
With respect to claim(s) 7, the claims relate to a specified format for the analysis results. As performed by a person, these steps appear to refer to the administrative process of formatting the results of the mental process. No additional limitation is present.
With respect to claim(s) 8, the claims relate to storing and analyzing a specific message related to a product. As performed by a person, these steps appear to refer to the mental and clerical process of selecting a message based on a predetermined criteria and performing a related analysis. No additional limitation is present.
With respect to claim(s) 9 and 19, the claims relate to responding to a question within the classified messages. As performed by a person, these steps appear to refer to the mental process of providing a response to a question in a specific category. No additional limitation is present.
With respect to claim(s) 10, the claims relate to generating responses from a dataset provided by the host. As performed by a person, these steps appear to refer to the mental process of answering questions based on known answers. No additional limitation is present.
With respect to claim(s) 11 and 20, the claims relate to alternative sources of information for an answer provided to a question. As performed by a person, these steps appear to refer to the mental process of using an information source (e.g., frequently asked questions, a library, etc.) to find an answer to a question. No additional limitation is present.
With respect to claim(s) 12, the claims relate to posting answers alongside questions in a publicly available format. As performed by a person, these steps appear to refer to the mental and clerical process of determining an answer to a question and providing that answer publicly (e.g., posted on a corkboard in a public space for attendees of the event). No additional limitation is present.
With respect to claim(s) 13, the claims relate to providing a question which couldn’t be answered to a secondary site. As performed by a person, these steps appear to refer to the mental and clerical process of determining a question could not be answered based on available information and handing the question to a second person.. No additional limitation is present.
These claims further do not remedy the judicial exception being integrated into a practical application and further fail to include additional elements that are sufficient to amount to significantly more than the judicial exception. As such, for the same reasons as described above with reference to independent claim(s) 1, 14, and 15, dependent claim(s) 2-13 and 16-20 are not patent eligible.
Appropriate correction is required.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-2, 5, 14-16 and 18 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Um (KR102283232B1, hereinafter Um).
Regarding claim 1, Um discloses A method executed by a computer device having at least one processor configured to execute computer-readable instructions stored in a memory (Systems and methods described with reference to “providing product information in real time through live video broadcasting in a video commerce system,” also referred to as the “x-caster application,” as implemented through the “broadcasting device,” which includes “a communication unit for transmitting and receiving wireless signals; an output unit for providing audio and/or video; and a processor functionally connected to the communication unit and the output unit” and “a storage (temporary or non-transitory storage device) (or memory) for performing methods or functions proposed in the present specification to be described later.”; Um, ¶ [0031], [0159]), comprising: classifying chat messages (“The broadcasting device may classify the query or inquiry in the chat window” and based on this selects “candidates (approximately 2 to 5 candidates)” for communicating with the seller where the broadcast device (and/or caster device) is controlled by the seller/broadcaster (e.g., using the x-caster application).; Um, ¶ [0407]-[0409]) received during a live broadcast of a host (The broadcasting device “provides a chat window related to the live video currently being broadcast so as to be distinguished from the live video,” as displayed “from the middle to the bottom of the live screen” such that “the user can check the chat contents by scrolling through the chat window,” the chat window including “the thumbnail, name, and chat details of the user who entered the chat.” As understood in the context of a live video, the chats received in the chat window are received during the “live video” the video being broadcast by the broadcaster/seller; Um, ¶ [0143], [0266]) using a function of a live commerce tool for the host (“The broadcasting device classifies questions or inquiries in the chat window examined earlier and, based on this, communicates with the seller” where classification in the chat window on the broadcast device is understood as part of the x-caster application, and therefore is understood as a native function of the live commerce tool.; Um, ¶ [0407]).
Regarding claim 2, Um discloses wherein the chat messages are classified into a category corresponding to message content (The system uses “a neural network model (e.g., the deep learning model 26) generated through a learning algorithm for data classification/recognition” where “classifies questions or inquiries in the chat window examined earlier and, based on this, communicates with the seller” regarding a related product, where the association of the question or inquiry to a product is a category; Um, ¶ [0103], [0407]-[0409]) using a language model (The system above can be implemented using “deep learning techniques such as neural networks (DBN, deep belief networks) and deep Q-networks, and can be applied to fields such as computer vision, speech recognition, natural language processing”; Um, ¶ [0101]).
Regarding claim 5, Um discloses wherein the method further comprises analyzing the chat messages received (“The broadcasting device may classify the query or inquiry in the chat window” and based on this selects “candidates (approximately 2 to 5 candidates)” for communicating with the seller where the broadcast device (and/or caster device) is controlled by the seller/broadcaster (e.g., using the x-caster application).; Um, ¶ [0407]) during the live broadcast in real time (The broadcasting device “provides a chat window related to the live video currently being broadcast so as to be distinguished from the live video,” as displayed “from the middle to the bottom of the live screen” such that “the user can check the chat contents by scrolling through the chat window,” the chat window including “the thumbnail, name, and chat details of the user who entered the chat.” As understood in the context of a live video, the chats received in the chat window are received during the “live video,” and in real time as they are responsive to the content of the live video, the video being broadcast by the broadcaster/seller; Um, ¶ [0143], [0266]) using the function of the live commerce tool (“The broadcasting device classifies questions or inquiries in the chat window examined earlier and, based on this, communicates with the seller” where classification in the chat window on the broadcast device is understood as part of the x-caster application, and therefore is understood as a native function of the live commerce tool.; Um, ¶ [0407]) and providing analysis results (the system receives the “conversation content between the seller and the selected candidates,” and then the “AI device” which may be part of the broadcast device, “extracts information about the product, information about price comparison, information about the seller in the video, location information, etc.{analysis results}” and the “broadcasting device can provide information received from the AI device together when providing product information”; Um, ¶ [0409]-[0410]).
Regarding claim 14, Um discloses A non-transitory computer-readable recording medium storing a computer program for execution the method of claim 1 on a computer device (Systems and methods described with reference to “providing product information in real time through live video broadcasting in a video commerce system,” also referred to as the “x-caster application,” as implemented through the “broadcasting device,” which includes “a communication unit for transmitting and receiving wireless signals; an output unit for providing audio and/or video; and a processor functionally connected to the communication unit and the output unit” and “a storage (temporary or non-transitory storage device) (or memory) for performing methods or functions proposed in the present specification to be described later.”; Um, ¶ [0031], [0159]) for execution the method of claim 1 on a computer device (See mapping of claim 1 with respect to Um, presented above).
Regarding claim 15, Um discloses A computer device comprising: at least one processor configured to execute computer-readable instructions included in a memory (Systems and methods described with reference to “providing product information in real time through live video broadcasting in a video commerce system,” also referred to as the “x-caster application,” as implemented through the “broadcasting device,” which includes “a communication unit for transmitting and receiving wireless signals; an output unit for providing audio and/or video; and a processor functionally connected to the communication unit and the output unit” and “a storage (temporary or non-transitory storage device) (or memory) for performing methods or functions proposed in the present specification to be described later.”; Um, ¶ [0031], [0159]), wherein the at least one processor is configured to classify chat messages (“The broadcasting device may classify the query or inquiry in the chat window” and based on this selects “candidates (approximately 2 to 5 candidates)” for communicating with the seller where the broadcast device (and/or caster device) is controlled by the seller/broadcaster (e.g., using the x-caster application).; Um, ¶ [0407]-[0409]) received during a live broadcast of a host (The broadcasting device “provides a chat window related to the live video currently being broadcast so as to be distinguished from the live video,” as displayed “from the middle to the bottom of the live screen” such that “the user can check the chat contents by scrolling through the chat window,” the chat window including “the thumbnail, name, and chat details of the user who entered the chat.” As understood in the context of a live video, the chats received in the chat window are received during the “live video” the video being broadcast by the broadcaster/seller; Um, ¶ [0143], [0266]) using a function of a live commerce tool for the host (“The broadcasting device classifies questions or inquiries in the chat window examined earlier and, based on this, communicates with the seller” where classification in the chat window on the broadcast device is understood as part of the x-caster application, and therefore is understood as a native function of the live commerce tool.; Um, ¶ [0407]).
Regarding claim 16, the rejection of claim 15 is incorporated. Claim 16 is substantially the same as claim 2 and is therefore rejected under the same rationale as above.
Regarding claim 18, the rejection of claim 15 is incorporated. Claim 18 is substantially the same as claim 5 and is therefore rejected under the same rationale as above.
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.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Um as applied to claim 1 above, and further in view of Non-patent literature to Min (Min, S., Lewis, M., Hajishirzi, H. and Zettlemoyer, L., 2021. Noisy Channel Language Model Prompting for Few-Shot Text Classification. arXiv preprint arXiv:2108.04106v2, hereinafter Min).
Regarding claim 3, the rejection of claim 1 is incorporated. Um discloses all of the elements of the current invention as stated above. However, Um fails to expressly recite wherein the classifying of the chat messages comprises: constructing a prompt for a target message using example data that includes a message example and a category of the message example; and generating a category of the target message according to a pattern of the example data by using the prompt as input to a language model.
Min teaches systems and methods of few-shot learning for text classification. (Min, ¶ Abstract). Regarding claim 3, Min teaches wherein the classifying of the chat messages comprises: constructing a prompt for a target message using example data that includes a message example and a category of the message example (“if the task is sentiment analysis with C = {c+,c−}, an example input text x would be ‘A three-hour cinema master class’” and “In a few-shot setup, we are also given a set of K training examples D={(x1,c1),···,(xK,cK)},” where “X is the set of all natural language texts and C = {c1...cm} is a set of labels.”; Min, ¶ p. 3, col. 1, lines 1-4; col. 2, lines 1-6); and generating a category of the target message according to a pattern of the example data by using the prompt as input to a language model (The “key idea is to prepend a concatenation of K training examples to the input so that a language model can learn the task setup from the input.” Thus, as the input includes K training examples with the set of labels corresponding to the category and the corresponding natural language texts, the example input text X will receive a generated category for the example input text X, according to the pattern established by the K training examples.; Min, ¶ p. 3 col. 2, lines 18-28).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the live commerce broadcasting systems of Um to incorporate the teachings of Min to include wherein the classifying of the chat messages comprises: constructing a prompt for a target message using example data that includes a message example and a category of the message example; and generating a category of the target message according to a pattern of the example data by using the prompt as input to a language model. Um discloses automated classification of queries and inquiries using a language model as part of an e-commerce interface. However, Um is silent regarding the construction of a prompt with example data for said classification. Min teaches a few-shot learning method for text classification where a prompt is constructed using concatenated examples of text and their corresponding categories, which is then received by the language model. The incorporation of the few-shot learning method of Min would allow the live commerce chat classifier of Um to adapt to new, custom classification categories dynamically, without the costs or time constraints required for retraining or fine-tuning the underlying language model, as understood in light of the disclosure of Min. (Min, ¶ Abstract; pg. 2, col. 2, lines 5-22).
Claim(s) 4 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Um as applied to claims 1 and 15 above, and further in view of Matsuoka (U.S. Pat. App. Pub. No. 2023/0066403, hereinafter Matsuoka).
Regarding claim 4, the rejection of claim 1 is incorporated. Um discloses all of the elements of the current invention as stated above. Um further discloses wherein the classifying of the chat messages comprises: setting a category that is a classification item of the chat messages for the live broadcast (“The above broadcasting device can display a list of products included in a live broadcast registered in X-caster.”; Um, ¶ [0138]); and classifying the chat messages into the set category… (The system uses “a neural network model (e.g., the deep learning model 26) generated through a learning algorithm for data classification/ recognition” where “classifies questions or inquiries in the chat window examined earlier and, based on this, communicates with the seller” regarding a related product, where the association of the question or inquiry to a product is a set category; Um, ¶ [0103], [0407]-[0409]). However, Um fails to expressly recite displaying the set category and the chat messages through an interface screen configured with a template of the category.
Matsuoka teaches systems and methods for sorting of projects and tasks based on “dynamic analysis and presentation of messages in a real-time chat stream”. (Matsuoka, ¶ [0002]). Regarding claim 4, Matsuoka teaches displaying the set category and the chat messages through an interface screen configured with a template of the category (“The UI management system 1636 can use... system settings to customize the UI display of the chat flow 1604” where, in response to “a single chat flow with messages associated with a wide variety of tasks or topics” the system can use “dynamic automated chat flow customization to create multiple chat flows, with each chat flow having a separate chat scroll interface (e.g., separate chat flows or chat flow displays)... to dynamically determine how messages are divided between chat flows, and when to separate messages that are in a single chat flow into multiple chat flows,” including sorting and grouping “messages in the chat flow... by activity.” and, as shown in FIG. 6, the sorted visually distinct containers have a clearly labeled category.; Matsuoka, ¶ [0112], [0179], FIG. 6).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the live commerce broadcasting systems of Um to incorporate the teachings of Matsuoka to include displaying the set category and the chat messages through an interface screen configured with a template of the category. Um discloses automated classification of queries and inquiries using a language model as part of an e-commerce interface. However, Um is silent regarding the above described GUI elements. The message filtering and management systems of Matsuoka allow for “dynamic analysis and presentation of messages in a real-time chat stream” which “can be applied to facilitate identification and creation of tasks” which results in a “chat stream presentation of information related to the tasks that may be performed for the benefit of a member using information from the chat streams,” which, as applied to the live commerce system of Um, would provide the known benefit of sorting relevant messages from irrelevant message based on topic, which allows the host to respond to related questions and increases the response rate for viewers, as recognized by Matsuoka. (Matsuoka, ¶ [0002]-[0003], [0009]).
Regarding claim 17, the rejection of claim 15 is incorporated. Claim 17 is substantially the same as claim 4 and is therefore rejected under the same rationale as above.
Claim(s) 6-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Um as applied to claim 1 above, and further in view of Berger (U.S. Pat. App. Pub. No. 2010/0325112, hereinafter Berger).
Regarding claim 6, the rejection of claim 5 is incorporated. Um discloses all of the elements of the current invention as stated above. However, Um fails to expressly recite wherein the providing of the analysis results comprises visualizing positive and negative reaction rates based on the classification results of the chat messages.
Berger teaches an electronic message management system for categorizing messages based on intent. (Berger, ¶ [0002], [0018]). Regarding claim 6, Berger teaches wherein the providing of the analysis results comprises visualizing positive and negative reaction rates based on the classification results of the chat messages (“An overall intent positiveness identification is performed at 46” which includes grouping based on at least “(1) expression of a positive opinion” and “(2) expression of a negative opinion” {positive and negative reaction...} and that “partitioned and grouped messages may be displayed” as “talkboards 74,” which can “include various bars 76 that represent a percentile {rates...} relating to a particular grouping {based on the classification results of the chat message...}.”; Berger, ¶ [0022], [0026]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the live commerce broadcasting systems of Um to incorporate the teachings of Berger to include wherein the providing of the analysis results comprises visualizing positive and negative reaction rates based on the classification results of the chat messages. Berger provides an electronic message management system which can visualize groups of categorized messages based on the proportion or rate of users expressing a specific sentiment, which may further be related to one or more products, which provides the known benefit of allowing a live commerce host, such as disclosed in Um, further insight into how the commerce-based event is being received by the audience in real time, such that the host can adjust or respond dynamically during the live event, capitalize on discovered insights, and address specific problems or issues during the event, as understood in light of the disclosure of Berger. (Berger, ¶ [0002], [0006], [0022]).
Regarding claim 7, the rejection of claim 5 is incorporated. Um discloses all of the elements of the current invention as stated above. However, Um fail(s) to expressly recite wherein the providing of the analysis results comprises generating and providing highlighted information related to a specific classification item based on the classification results of the chat messages.
The relevance of Berger is described above with relation to claim 6. Regarding claim 7, Berger teaches wherein the providing of the analysis results comprises generating and providing highlighted information related to a specific classification item (Discloses “The talkboards 74 include various bars 76 that represent a percentile relating to a particular grouping” and “the larger the bar 76 the more senders of messages incorporated a particular feature in their respective messages,” where the system can provide further subcategorization information based on user selection of the category level groupings. As described with reference to an example, when the user selects the “coffee-latte” and “water-bottle” bars 76, the system presents “in the first column, all intentions (bars) related to bar coffee-latte and the bar water-bottle as well as in third column all bars representing if those groups of people gave an explanation, contradiction, etc.” which is highlighted information related to the specific classification item.; Berger, ¶ [0026]-[0028]) based on the classification results of the chat messages (All subclassification data and related information is necessarily derived from the groupings of the messages 22 (e.g., explanations related to “coffee-latte” necessarily derive from and incorporate the grouping of “coffee latte”, etc.), thus is based on the classification results of the chat messages; Berger, ¶ [0021]-[0022], [0026]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the live commerce broadcasting systems of Um to incorporate the teachings of Berger to include wherein the providing of the analysis results comprises generating and providing highlighted information related to a specific classification item based on the classification results of the chat messages. Berger provides an electronic message management system which can visualize groups of categorized messages based on the proportion or rate of users expressing a specific sentiment, which may further be related to one or more products, which provides the known benefit of allowing a live commerce host, such as disclosed in Um, further insight into how the commerce-based event is being received by the audience in real time, such that the host can adjust or respond dynamically during the live event, capitalize on discovered insights, and address specific problems or issues during the event, as understood in light of the disclosure of Berger. (Berger, ¶ [0002], [0006], [0022]).
Regarding claim 8, the rejection of claim 5 is incorporated. Um discloses all of the elements of the current invention as stated above. However, Um fail(s) to expressly recite wherein the providing of the analysis results comprises storing a message of a specific classification item based on the classification results of the chat messages, and the message of the specific classification item is used as analysis data related to the host’s product.
The relevance of Berger is described above with relation to claim 6. Regarding claim 8, Berger teaches wherein the providing of the analysis results comprises storing a message of a specific classification item based on the classification results of the chat messages (“The electronic device 104 receives messages at 124. Those messages are stored 126 in the memory 108 {storing a message of a specific classification item...}” and the “control unit 106 partitions the messages at 128” where the “partitioning of the messages divides the messages, as is discussed in greater detail above, into segments having similar elements. {...based on the classification results of the chat messages}”; Berger, ¶ [0035]), and the message of the specific classification item is used as analysis data related to the host’s product (Though Berger fails to expressly recite a host related to the product, the system includes the analysis of message data with relation to specified products (e.g., “coffee latte” or “water bottle”), which as applied to the host product in Um, would be understood as analysis data related to the host’s product when performed with relation to the “questions or inquiries in the chat window” for the live commerce system of Um.; Berger, ¶ [0035]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the live commerce broadcasting systems of Um to incorporate the teachings of Berger to include wherein the providing of the analysis results comprises storing a message of a specific classification item based on the classification results of the chat messages, and the message of the specific classification item is used as analysis data related to the host’s product. Berger provides an electronic message management system which can visualize groups of categorized messages based on the proportion or rate of users expressing a specific sentiment, which may further be related to one or more products, which provides the known benefit of allowing a live commerce host, such as disclosed in Um, further insight into how the commerce-based event is being received by the audience in real time, such that the host can adjust or respond dynamically during the live event, capitalize on discovered insights, and address specific problems or issues during the event, as understood in light of the disclosure of Berger. (Berger, ¶ [0002], [0006], [0022]).
Claim(s) 9-11 and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Um as applied to claim 1 and 15 above, and further in view of Patel (U.S. Pat. App. Pub. No. 2018/0329982, hereinafter Patel).
Regarding claim 9, the rejection of claim 1 is incorporated. Um discloses all of the elements of the current invention as stated above. However, Um fails to expressly recite further comprising providing an automatic response to an inquiry message classified into an inquiry category among the chat messages using the function of the live commerce tool.
Patel teaches systems and methods for “providing intelligent response suggestions to messages including unstructured natural language information.” (Patel, ¶ [0002]). Regarding claim 9, Patel teaches further comprising providing an automatic response to an inquiry message classified into an inquiry category among the chat messages using the function of the live commerce tool (Discloses a “digital assistant 800” including “a natural language analyzer 820, a query evaluator 840, a predicted response evaluator 860, and a predicted response generator 880” which “can receive one or more messages 802 that include unstructured natural language information” which may be a query {an inquiry message} classified in “the category of generic queries {classified into an inquiry category}” and the “query category can be associated with a plurality of sets of candidate predicted responses” which is applied to modify the live commerce tool of Um using the chat messages described therein. {using the function of the live commerce tool}; Patel, ¶ [0248], [0251], [0256], [0258]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the live commerce broadcasting systems of Um to incorporate the teachings of Patel to include further comprising providing an automatic response to an inquiry message classified into an inquiry category among the chat messages using the function of the live commerce tool. The intelligent messaging systems of Patel can receive incoming messages and classify them into query categories for the automatic provision of a predicted response, which would be understood as a natural modification of the live commerce systems of Um to achieve the benefit of automatically triaging and answering expected viewer inquiries (e.g., shipping costs, standard product information, etc.) during a live broadcast, which reduces the host’s cognitive load and allows them to focus on the presentation and/or more nuanced questions in a fast moving chat, as recognized in the context of the disclosure of Patel. (Patel, ¶ [0004], [0006]).
Regarding claim 10, the rejection of claim 9 is incorporated. Um discloses all of the elements of the current invention as stated above. However, Um fail(s) to expressly recite wherein the automatic response is provided based on a response dataset provided in advance by the host.
The relevance of Patel is described above with relation to claim 9. Regarding claim 10, Patel teaches wherein the automatic response is provided based on a response dataset (“a query category can be associated with a plurality of sets of candidate predicted responses” where “after digital assistant 800 receives message 802C... it can provide one set of predicted responses, from the plurality of sets of candidate predicted responses”; Patel, ¶ [0257]) provided in advance by the host (Discloses deriving the plurality of sets from “stored messages” which can be “messages collected from the past conversations” as well as based on elicited “additional input,” received “via a natural language dialogue or other user interfaces upon request by DA server 106” and “the stored messages in first contexts 1002 can include at least one query corresponding to one or more query categories.” In the context of Um, the elicited “additional input” is understood to come from the host {provided in advance by the host}.; Patel, ¶ [0085], [0261]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the live commerce broadcasting systems of Um to incorporate the teachings of Patel to include wherein the automatic response is provided based on a response dataset provided in advance by the host. The intelligent messaging systems of Patel can receive incoming messages and classify them into query categories for the automatic provision of a predicted response, which would be understood as a natural modification of the live commerce systems of Um to achieve the benefit of automatically triaging and answering expected viewer inquiries (e.g., shipping costs, standard product information, etc.) during a live broadcast, which reduces the host’s cognitive load and allows them to focus on the presentation and/or more nuanced questions in a fast moving chat, as recognized in the context of the disclosure of Patel. (Patel, ¶ [0004], [0006]).
Regarding claim 11, the rejection of claim 9 is incorporated. Um discloses all of the elements of the current invention as stated above. However, Um fail(s) to expressly recite wherein the automatic response is provided based on at least one of the host’s product information, a dataset converted from the host’s voice through speech to text (STT), and a dataset accumulated from the host’s previous broadcast.
The relevance of Patel is described above with relation to claim 9. Regarding claim 11, Patel teaches wherein the automatic response is provided based on at least one of the host’s product information, a dataset converted from the host’s voice through speech to text (STT), and a dataset accumulated from the host’s previous broadcast (the plurality of sets of candidate predicted responses being derived from “stored messages” which can be “messages collected from the past conversations” as well as based on elicited “additional input,” received “via a natural language dialogue or other user interfaces upon request by DA server 106” and “based on the unstructured natural language information contained in messages 802, natural language analyzer 820 obtains unstructured natural language texts and determines token sequences according to semantics, syntax, and/or punctuation marks associated with the unstructured natural language texts” and “can perform speech-to-text conversion to obtain texts (e.g., token sequences)”; Patel, ¶ [0085], [0249], [0257], [0261]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the live commerce broadcasting systems of Um to incorporate the teachings of Patel to include wherein the automatic response is provided based on at least one of the host’s product information, a dataset converted from the host’s voice through speech to text (STT), and a dataset accumulated from the host’s previous broadcast. The intelligent messaging systems of Patel can receive incoming messages and classify them into query categories for the automatic provision of a predicted response, which would be understood as a natural modification of the live commerce systems of Um to achieve the benefit of automatically triaging and answering expected viewer inquiries (e.g., shipping costs, standard product information, etc.) during a live broadcast, which reduces the host’s cognitive load and allows them to focus on the presentation and/or more nuanced questions in a fast moving chat, as recognized in the context of the disclosure of Patel. (Patel, ¶ [0004], [0006]).
Regarding claim 19, the rejection of claim 15 is incorporated. Claim 19 is substantially the same as claim 9 and is therefore rejected under the same rationale as above.
Regarding claim 20, the rejection of claim 19 is incorporated. Claim 20 is substantially the same as claim 11 and is therefore rejected under the same rationale as above.
Claim(s) 12 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Um and Patel as applied to claim 9 above, and further in view of Stinchcomb (U.S. Pat. App. Pub. No. 2011/0106662, hereinafter Stinchcomb).
Regarding claim 12, the rejection of claim 9 is incorporated. Um and Patel disclose all of the elements of the current invention as stated above. However, Um fails to expressly recite wherein the providing of the automatic response comprises automatically posting an inquiry and a corresponding response to a bulletin board related to the host’s product for the inquiry message to which the automatic response was successfully generated.
Stinchcomb teaches an interactive online shopping platform with a dedicated question queue. (Stinchcomb, ¶ [0006], [0024]). Regarding claim 12, Stinchcomb teaches wherein the providing of the automatic response comprises automatically posting an inquiry and a corresponding response to a bulletin board related to the host’s product for the inquiry message to which the automatic response was successfully generated (“FIG. 14 illustrates a question queue 425 that may be accessed by an event moderator, host, or administrator. The question queue may list questions, the username of the member who submitted the question, and an amount of time that had elapsed since the question was posted. The event moderator, host, or administrator may have the option to answer questions in the queue by posting an answer that is viewable to all members participating in the event, if they feel the question is directed to something all in the room might wish to know,” where the location receiving the posted question and answer that is “viewable to all members” is the bulletin board, and the answer was successfully generated as explained with reference to Patel in claim 9 (where said generation occurred); Stinchcomb, ¶ [0192], FIG. 14).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the live commerce broadcasting systems of Um, as modified by the automated response systems of Patel, to incorporate the teachings of Stinchcomb to include wherein the providing of the automatic response comprises automatically posting an inquiry and a corresponding response to a bulletin board related to the host’s product for the inquiry message to which the automatic response was successfully generated. The combination of Um and Patel teaches a live commerce system that automatically generates responses to chat inquiries. However, the combination of Um and Patel fail to disclose a specified location for receipt of questions, as opposed to general chat discussions. The dedicated “question queue” of Stinchcomb, which Stinchcomb distinguishes from the general chat feed, provides for both a specified location for questions to be answered by the automated question answering systems of Patel, and possible pinning of the question and answer pairs, based on expected value to the audience described in Stinchcomb and Um, resulting in both a more accessible format for question answering, and reduced question answering load due to the availability of a bulletin board for questions of general value to the audience, as recognized by Stinchcomb. (Stinchcomb, ¶ [0192]).
Regarding claim 13, the rejection of claim 12 is incorporated. Um and Patel disclose all of the elements of the current invention as stated above. However, Um fail(s) to expressly recite wherein the providing of the automatic response comprises providing the inquiry message to which a generation of the automatic response has failed through a separate interface.
The relevance of Patel is described above with relation to claim 9. Regarding claim 13, Patel teaches wherein the providing of the automatic response comprises providing the inquiry message to which a generation of the automatic response has failed (“When a respective event recognizer 280 determines that the series of sub-events do not match any of the events in event definitions 286, the respective event recognizer 280 enters an event impossible, event failed, or event ended state”; Patel, ¶ [0146]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the live commerce broadcasting systems of Um to incorporate the teachings of Patel to include wherein the providing of the automatic response comprises providing the inquiry message to which a generation of the automatic response has failed. The intelligent messaging systems of Patel can receive incoming messages and classify them into query categories for the automatic provision of a predicted response, which would be understood as a natural modification of the live commerce systems of Um to achieve the benefit of automatically triaging and answering expected viewer inquiries (e.g., shipping costs, standard product information, etc.) during a live broadcast, which reduces the host’s cognitive load and allows them to focus on the presentation and/or more nuanced questions in a fast moving chat, as recognized in the context of the disclosure of Patel. (Patel, ¶ [0004], [0006]). However, Um and Patel fail(s) to expressly recite providing the inquiry message...through a separate interface.
The relevance of Stinchcomb is described above with relation to claim 12. Regarding claim 13, Stinchcomb teaches providing the inquiry message...through a separate interface (“FIG. 14 illustrates a question queue 425 that may be accessed by an event moderator, host, or administrator. The question queue may list questions, the username of the member who submitted the question, and an amount of time that had elapsed since the question was posted” where the question queue is a separate interface from the chat window (e.g., as described in the context of a chat room); Stinchcomb, ¶ [0074], [0192], FIG. 14).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the live commerce broadcasting systems of Um, as modified by the automated response systems of Patel, to incorporate the teachings of Stinchcomb to include providing the inquiry message...through a separate interface. The combination of Um and Patel teaches a live commerce system that automatically generates responses to chat inquiries. However, the combination of Um and Patel fail to disclose a specified location for receipt of questions, as opposed to general chat discussions. The dedicated “question queue” of Stinchcomb, which Stinchcomb distinguishes from the general chat feed, provides for both a specified location for questions to be answered by the automated question answering systems of Patel, and possible pinning of the question and answer pairs, based on expected value to the audience described in Stinchcomb and Um, resulting in both a more accessible format for question answering, and reduced question answering load due to the availability of a bulletin board for questions of general value to the audience, as recognized by Stinchcomb. (Stinchcomb, ¶ [0192]).
Conclusion
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/Sean E Serraguard/Primary Examiner, Art Unit 2657
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