CTNF 19/049,394 CTNF 80767 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia 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 § 103 07-20-aia AIA 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. 07-21-aia AIA Claim s 1, 3-4, 9-13, 16-17 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Choudhury et al. – hereinafter Choudhury (US 2022/0391928) in view of Wood (US 2021/0208744) As per claim 1, Choudhury discloses a computer-implemented method for responding to a social media post, comprising: receiving, via a chatbot of one or more processors, a social media post; ([0020] An author may be a social media platform user who has posted some content from a social media platform handle. This handle can be a personal user's handle, or a brand's handle.) categorizing, via the chatbot, the social media post, wherein the categorizing comprises determining a category of the social media post, the category comprising: (i) customer complaint about a company; or (ii) customer complaint about a product and/or service; ([0030] During-experience phase of the experience phase profile may relate to a user's actions and activity that may be needed while using the products. In case of an airline brand the during-experience keywords may include check in procedures, baggage handling, cabin experience, flight timings etc. [0031] Post experience phase of the experience phase profile may relate to a user's actions and activity that may be needed after the actual use by a user. In case of an airline brand the post experience keywords may relate to lost baggage, delayed landings etc.; [0032] In an embodiment, an at-risk profile may represent keywords associated with complaints, negative experiences and similar related topics.) determining, via the chatbot, based upon the categorization, an entity to contact; and [0032] In an embodiment, an at-risk profile may represent keywords associated with complaints, negative experiences and similar related topics. This may help identify posts by an unhappy customer, and accordingly a brand can identify if it may lose a regular or old customer) in response to the determining the category of the social media post to be (i) the customer complaint about the company or (ii) the customer complaint about a product and/or service: building, via the chatbot, based upon the determined entity to contact, a response to the social media post and ([0049] In an embodiment, identifying these influencers may help in prioritizing response, content modification and mitigation of negative virality. It may help a brand prioritize while responding to its users based on who is a strong influencer. For campaign it may help in targeted social media ads and engagement, by identifying bigger influencer posting positively about the industry. [0050] Once the extracted data is analyzed and categorized into campaign data, True social data, news data, and other identified data and analysis explained above, these may be stored within the social content database (203) as a curated data (203.2)) sending, via the chatbot, the response to the entity. ([0060] The brands may decide to take appropriate corrective actions for customers based on the dashboards. The dashboards are accessed by Acting component (600) which may be configured to help out or notify the brand's designated person/s, concerned users or sections in the brands to take a required action as required. The notification can be mail based, or any other appropriate for) Choudhury fails to disclose the response including a summary of the social media post, or a quotation from the social media post. Wood discloses the response including a summary of the social media post, or a quotation from the social media post. ([0021]; FIG. 1A illustrates an exemplary main area 112 displaying a plurality of posts in which each post comprises a summary of content of a more complete post, while FIG. 1B illustrates an exemplary main area 112A in which a post is selected and the entire content from the selected post is displayed in full to the user.) It would have been obvious before the earliest effective filing date for the teachings of Chowdhury to be modified so that the response includes the summary of the social media post. This would have been beneficial to permit a user to navigate through the content in a logical and easy manner. (Wood[0021]]) As per claim 3, Choudhury / Wood disclose the computer-implemented method of claim 1. Wood discloses wherein the built response includes the summary of the social media post. ([0021]; FIG. 1A illustrates an exemplary main area 112 displaying a plurality of posts in which each post comprises a summary of content of a more complete post, while FIG. 1B illustrates an exemplary main area 112A in which a post is selected and the entire content from the selected post is displayed in full to the user.) As per claim 4, Choudhury / Wood disclose the computer-implemented method of claim 1. wherein the built response includes the quotation from the social media post. (Fig .1 A; item 112; initial lines of the post) As per claim 9 and 16, please see the discussion under claim 1 as similar logic applies. As per claim 10, please see the discussion under claim 2 as similar logic applies. As per claims 11 and 17, please see the discussion under claim 3 as similar logic applies. As per claim 12, please see the discussion under claim 4 as similar logic applies. As per claim 13, Choudhury / Wood disclose the computer system of claim 9. Choudhury discloses wherein the computer system further comprises a display device, and wherein the one or more processors are further configured to display the response on the display device. ([0015]; Output controller 110 may be operatively coupled (e.g., via a wired or wireless connection) to a display device (e.g., a monitor, television, mobile device screen, touch-display, etc.) in such a fashion that output controller 110 can transform the display on display device (e.g., in response to modules executed). ) As per claim 19, Choudhury / Wood disclose the computer system of claim 16. Choudhury discloses wherein the determining the category comprises determining the category to be the customer complaint about the product and/or service. ([0032] In an embodiment, an at-risk profile may represent keywords associated with complaints, negative experiences and similar related topics. This may help identify posts by an unhappy customer, and accordingly a brand can identify if it may lose a regular or old customer. Some keywords may be ‘never use again’, ‘last experience’, one of the worst etc.) As per claim 20, please see the discussion under claim 13 as similar logic applies . 07-21-aia AIA Claim s 2, 5-6, 14-15 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Choudhury (US 20220391928) / Wood (US 2021/0208744) further in view of Alfia et al. – hereinafter Alfia (US 2023/0289816) As per claim 2, Choudhary / Wood disclose the computer-implemented method of claim 1. The combined teachings of Choudhary / Wood fail to disclose further including: further in response to the determining the category of the social media post to be (i) the customer complaint about the company or (ii) the customer complaint about a product and/or service, determining the entity to contact be a representative of the company. Alfia discloses further including: further in response to the determining the category of the social media post to be (i) the customer complaint about the company or (ii) the customer complaint about a product and/or service, determining the entity to contact be a representative of the company. ( [0025]; Also, there is no inherent manner to escalate the issue/problem when the customer expresses it to an employee or manager when the issue/problem cannot be adequately handled, resolved, or corrected by the business employee or manager or others in the business who need to know about the issue/problem and any mitigation, resolution, or correction enacted by the business. ) It would have been obvious before the earliest effective filing date of the invention for the combined teachings of Choudhary / Wood to be modified so that the representative of the company is contacted upon customers concerns of chat. This would have enabled to resolve issues in real-time. As per claim 5, Choudhury / Wood disclose the computer-implemented method of claim 1, Alfia discloses further comprising training the chatbot with a historical dataset comprising: (i) historical social media posts, and/or (ii) historical responses to the historical social media posts. ([0061]; An example of a chat history button 506B gives a user access to previous chat transcripts and interactions from users. One example of a manage employees button 506 C might display an interactive list of current and past employees utilizing the feedback system. A user could potentially use this example to access the feedback history or chat history of each employee. [0070]; The AI score may be determined by using Google's AI (Artificial Intelligence) API or other similar services to assign a score of 0-100 to the initial Feedback that a user sends. Google's AI looks for key words in the Feedback and gives us back a rating. In these and similar examples, the key words may be Feedback system defined, user defined, or Google AI defined. The feedback system can then convert that rating on a 0-100 scale to help the business determine the user's sentiment at the time that the Feedback was submitted.) As per claim 6, Choudhury / Wood disclose the computer-implemented method of claim 1. Alfia discloses wherein the chatbot includes: an artificial intelligence (AI) chatbot, a machine learning (ML) chatbot, a generative AI chatbot, a deep learning algorithm, a generative pre-trained transformer (GPT), and/or long-short-term- memory (LSTM). ([0070]; The AI score may be determined by using Google's AI (Artificial Intelligence) API or other similar services to assign a score of 0-100 to the initial Feedback that a user sends. Google's AI looks for key words in the Feedback and gives us back a rating. In these and similar examples, the key words may be Feedback system defined, user defined, or Google AI defined. The feedback system can then convert that rating on a 0-100 scale to help the business determine the user's sentiment at the time that the Feedback was submitted.) As per claim 14, please see the discussion under claim 5 as similar logic applies. As per claim 15, please see the discussion under claim as similar logic applies. As per claim 18, Choudhury / Wood disclose the computer system of claim 16. Alfia discloses wherein the determining the category comprises determining the category to be the customer complaint about the company. ([0094]; Furthermore, the Artificial Intelligence (AI) layer of the program lets businesses know what categories of issues their customers are submitting problems/issues for and the severity of the positive or negative experience the customer is having with the company when submitting the problem/issue information.) 07-21-aia AIA Claim s 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Choudhury (US 20220391928) / Wood (US 2021/0208744) further in view of Rugel et al. - hereinafter Rugel (US 2019/0095822) As per claim 7, Choudhury / Wood disclose the computer-implemented method of claim 1. The combined teachings of Choudhury / Wood fail to disclose wherein the building the response includes building the response to include a recommendation to purchase an additional product and/or service including a homeowners insurance policy, a renters insurance policy, an auto insurance policy, a life insurance policy and/or a disability insurance policy. Rugel disclose wherein the building the response includes building the response to include a recommendation to purchase an additional product and/or service including a homeowners insurance policy, a renters insurance policy, an auto insurance policy, a life insurance policy and/or a disability insurance policy. ([0033]; In other examples, external data computing device 140 may store or provide access to social data related to users, such as social media posts from social networking services, email messages, text messages, chats, images related thereto, phone calls, contacts, social media friends and/or connections, etc. In some examples, the external data computing device 140 is a computing device of an individual associated with the user (e.g., a friend, connection, relative, individual having a device connected to a device of the user, etc.) and participating in a service provided by the multi- source data evaluation and control system.; Additional information, such as the user's email address, social media account information, and authorization to collect information may also be received. The information may be transmitted from the local user computing devices 150, 155, remote user mobile computing device 170, remote user computing device 175, or the like, to the multi-source data evaluation and control computing platform 110 and may be processed by the product identification module 112a to identify one or more products (e.g., a life insurance policy) to offer or recommend to the user. In some examples, interactive tests used to determine eligibility for the one or more products may be identified based on the identified one or more products, as will be discussed more fully herein It would have been obvious before the effective filing date of the invention for the combined teachings of Choudhury / Wood to be modified so that the chatbot reviews the social media chat messages to build the recommendations of insurance policies to the users using artificial intelligence. This would have made it easier to evaluate the risks of a person associated with an insurance policy and offer incentive to users to buy insurance. As per claim 8, Choudhury / Wood disclose the computer-implemented method of claim 7. Rusel discloses wherein the chatbot is trained based upon: a historical dataset comprising: (i) historical social media posts, and/or (ii) historical responses to the historical social media posts; and historical insurance customer profiles associated with the historical social media posts, the historical insurance customer profiles including information of historical homeowners insurance policies, historical renters insurance policies, historical auto insurance policies, historical life insurance policies, and/or historical disability insurance policies of historical insurance customers. (([0050]; The machine learning datasets 112k may be generated based on analyzed data (e.g., data from previously executed interactive condition evaluation tests, social data, historical data from internal and/or external sources, and the like), raw data, and/or data received from one or more outside sources.; [0051] The machine learning engine 112j may receive data (e.g., social data, social scores, social profiles, data collected during one or more interactive condition evaluation tests executed by and received from, for example, remote user mobile computing device 170, remote user computing device 175, or the like, internal data computing device 120, external data computing device 140, and the like) and, using one or more machine learning algorithms, may generate one or more machine learning datasets 112k.) Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent toapplicant's disclosure. See PTO-892 form . 07-101 Any inquiry concerning this communication or earlier communications from theexaminer should be directed to Chirag R Patel whose telephone number is (571)272-7966 . The examiner can normally be reached on Monday to Friday from 9:00AM to 6:00PM . If attempts to reach the examiner by telephone are unsuccessful, theexaminer's supervisor, Glenton Burgess , can be reached on 571-272-3949 . The fax phone number for the organization where this application or proceedingis assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status informationfor published applications may be obtained from either Private PAIR or PublicPAIR. Status information for unpublished applications is available throughPrivate PAIR only. For more information about the PAIR system, seehttp://pairdirect.uspto.gov. Should you have questions on access to the PrivatePAIR system, contact the Electronic Business Center (EBC) at 866-217-9197(toll free). /Chirag R Patel/ Primary Examiner, Art Unit 2454 Application/Control Number: 19/049,394 Page 2 Art Unit: 2454 Application/Control Number: 19/049,394 Page 3 Art Unit: 2454 Application/Control Number: 19/049,394 Page 4 Art Unit: 2454 Application/Control Number: 19/049,394 Page 5 Art Unit: 2454 Application/Control Number: 19/049,394 Page 6 Art Unit: 2454 Application/Control Number: 19/049,394 Page 7 Art Unit: 2454 Application/Control Number: 19/049,394 Page 8 Art Unit: 2454 Application/Control Number: 19/049,394 Page 9 Art Unit: 2454 Application/Control Number: 19/049,394 Page 10 Art Unit: 2454
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