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 .
1. This action is responsive to the application filed on 06/03/2024.
2. Claims 1-18 are pending.
3. Claims 1-18 are rejected.
Claim Objections
Claim 1 is objected to because of the following informalities: claim 1 contains the acronym “ID”. Appropriate correction is required.
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.
Claim 14 is 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 14 recites the limitation "wherein the AI employed…" in line 1. 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.
Claims 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because the “system” claims are not a process, machine, manufacture, or composition of matter.
The claim lacks the necessary physical articles / objects / elements / components / structure / hardware to constitute a machine or a manufacture within the meaning of 35 USC 101. They are clearly not a series of steps or acts to be a process nor are they a combination of chemical compounds to be a composition of matter. Therefore, the claimed subject matter as a whole fails to fall within the definition of a process, machine, manufacture or composition of matter, patentable eligible category subject matter.
For more information regarding 35 U.S.C 101 please see MPEP 2106 and section of 2106 titled “Non-limiting examples of claims that are not directed to one of the statutory categories: vi. a computer program per se, Gottschalk v. Benson, 409 U.S. at 72.”
Examiner suggests coupling the system with sufficient structure such as a processor/memory/etc.
Examiner’s Note:
The Examiner informs Applicant that once the 101 Rejection is overcome, a 112f and 112b Rejection would apply, since there is no corresponding hardware structure since there is no sufficient structure, material or acts to entirely perform the recited function.
Claim Rejections - 35 USC § 102
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.
Claims 1-4, 17, and 18 are rejected under 35 U.S.C. 102(a)(1) as being unpatentable by Heather Hopkins et al (WO 2021150771 A1), hereinafter “Hopkins”.
Regarding Claim 1, Hopkins discloses a dating application system (Hopkins, Paragraphs 0022-0023, online dating platforms is used as an example) comprising:
a frontend user interface (UI) configured for user interaction (Hopkins, Paragraph 0043, user has access to a user interface in order to view potential matches);
and a backend artificial intelligence (AI) engine comprising:
a Text Analysis module configured to scan messages for harmful language using natural language processing (NLP) algorithms (Hopkins, Paragraph 0032, artificial intelligence engine determines certain undesirable qualities (e.g., hostile, extreme nervousness when speaking, etc.). Paragraphs 0062, 0067, 0076, verification service analyzes video/images in order to determine if criteria are met. Paragraph 0053, several options are provided to the user in order to communicate, including video calling, text messaging, voice-only call, etc.);
a Video Analysis module configured to analyze live video streams for inappropriate visual content using computer vision techniques (Hopkins, Paragraph 0032, artificial intelligence engine determines certain undesirable qualities (e.g., hostile, extreme nervousness when speaking, etc.). Paragraphs 0062, 0067, 0076, verification service analyzes video/images in order to determine if criteria are met. Paragraph 0053, several options are provided to the user in order to communicate, including video calling, text messaging, voice-only call, etc.);
and a Report Management module configured to enable users to report inappropriate behavior and track reported incidents associated with user IDs (Hopkins, Paragraph 0053, users are provided with an interface that can be used to report other users for inappropriate language, inappropriate conversation, or actions taken during the conversation. The system will receive and store the option(s) selected by the user and take appropriate action).
Regarding Claim 2, Hopkins discloses the system of claim 1 above, wherein the Text Analysis module utilizes sentiment analysis and keyword matching to detect toxic language, and flags messages containing predefined keywords and phrases indicative of abusive or inappropriate behavior (Hopkins, Paragraph 0032, artificial intelligence engine determines certain undesirable qualities (e.g., hostile, extreme nervousness when speaking, etc.)).
Regarding Claim 3, Hopkins discloses the system of claim 1 above, wherein the Video Analysis module employs object detection and gesture recognition algorithms to identify nudity, obscene gestures, and other forms of visual harassment, and flags video interactions containing such content for review (Hopkins, Paragraph 0032, artificial intelligence engine determines certain undesirable qualities (e.g., hostile, extreme nervousness when speaking, etc.). Paragraph 0152, user can report other users for inappropriate behavior, such as nudity/sexual, underage, hate speech, spam, etc.).
Regarding Claim 4, Hopkins discloses the system of claim 1 above, wherein the Report Management module enables users to report inappropriate behavior through a user interface, specifying the type of behavior and providing additional details, and logs each report in a database associated with user IDs for comprehensive tracking (Hopkins, Paragraph 0053, users are provided with an interface that can be used to report other users for inappropriate language, inappropriate conversation, or actions taken during the conversation. The system will receive and store the option(s) selected by the user and take appropriate action. Paragraph 0148, report user interface used to enter a report on another participant. Figs 5Q(1)-5Q(3), Paragraphs 0150-0152, user interface which includes reasons to provide the cause of the report).
Regarding Claim 17, Hopkin discloses a method for facilitating dating matches between users online on a platform and mobile device application configured to mitigate inappropriate behavior (Hopkins, Paragraphs 0022-0023, online dating platforms is used as an example), the method comprising:
a server computer hosting a platform to a domain (Hopkins, Paragraph 0055, server);
users accessing the platform via the internet on a mobile device equipped with a camera and a microphone, referenced as user devices (Hopkins, Paragraph 0138, device contains camera and microphone);
the server computer suggesting matches to users for dates according to an algorithm, the algorithm informed by an analysis of users’ interests and time available for an online date (Hopkins, Paragraph 0041, generating match recommendations. For example, activity data, such as the number of times a user is selected by other users to engage in online communications with (optionally over a specified period of time), the number of times a user has engaged with another user using a first channel of electronic communication (e.g., video call), etc.);
wherein parameters of the algorithm dictate the suggestions of matches to users, the parameters including: gender, age, religion, ethnicity, location, and time available for a date (Hopkins, Paragraphs 0043-0044, user requests to view potential matches. The system filters out users whose profiles indicate that they are not in an acceptable geographical area (e.g., are outside of the desired location specified by the requesting user), and then filter out users that do not have the desired color hair, age, height, activity data, etc.);
a first user matching with a second user (Hopkins, Paragraphs 0043-0044, user requests to view potential matches.);
the second user agreeing to meet via an online date on the platform at a time posited by the first user and agreed to by the second user (Hopkins, Paragraph 0141, user is enabled to initiate and/or receive video calls with matching users);
the first user meeting the second user during a video call (Hopkins, Paragraph 0143, users join video call);
AI of the platform monitoring the video in real-time and analyzing the speech, mannerisms, posture, and gestures of both the first user and the second user to detect signs of inappropriate behavior (Hopkins, Paragraph 0032, artificial intelligence engine determines certain undesirable qualities (e.g., hostile, extreme nervousness when speaking, etc.). Paragraphs 0062, 0067, 0076, verification service analyzes video/images in order to determine if criteria are met.).
and Al flagging either the first user or the second user if inappropriate behavior is detected (Hopkins, Paragraph 0032, artificial intelligence engine determines certain undesirable qualities (e.g., hostile, extreme nervousness when speaking, etc.)).
Regarding Claim 18, Hopkins discloses the method of claim 17, wherein inappropriate behavior includes, but is not limited to:
typing or saying aloud predefined keywords indicating abuse and abusive posture as detected via AI visual analysis (Hopkins, Paragraph 0032, artificial intelligence engine determines certain undesirable qualities (e.g., hostile, extreme nervousness when speaking, etc.)).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 5, 6, and 9-16 are rejected under 35 U.S.C. 103 as being unpatentable over Hopkins in view of Marion Beaufrere et al (US 20140317732 A1), hereinafter “Beaufrere”.
Regarding Claim 5, Hopkins discloses the system of claim 1 above.
However, Hopkins fails to explicitly disclose further comprising: a severity scoring mechanism of said text analysis module configured to assign severity scores to reported incidents based on predefined criteria and patterns, including the frequency and severity of inappropriate language or actions; and an automated action mechanism configured to take actions such as issuing warnings, suspending accounts temporarily, or permanently banning users based on severity scores.
Beaufrere, from the same or similar field of endeavor, discloses further comprising:
a severity scoring mechanism of said text analysis module configured to assign severity scores to reported incidents based on predefined criteria and patterns, including the frequency and severity of inappropriate language or actions (Beaufrere, Paragraph 0029, reporting interface allows a user to report on somebody that present hate speech, nudity, malicious activity, etc. Paragraph 0036, disabled connectivity score calculating a disabled connectivity score for a user associated with a report of malicious activity or content. When a report of malicious activity or content is received by the social networking system, the disabled connectivity scoring module computes a disabled connectivity score for a target user or a target object (e.g., the reporting user or another user or object maintained by the social networking system and associated with the report));
and an automated action mechanism configured to take actions such as issuing warnings, suspending accounts temporarily, or permanently banning users based on severity scores (Beaufrere, Paragraph 0029, based on information about the report and the reported content or action, the social networking system determines a type of action to take in response to the report).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Hopkins in view of Beaufrere in order to further modify the method of online communications from the teachings of Hopkins with the method of categorizing social networking users from the teachings of Beaufrere.
One of ordinary skill in the art would have been motivated because analyzing the activities of the user the system will be able to determine the actions of the users, whether they are malicious or not (Beaufrere – Paragraphs 0001-0003, 0012).
Regarding Claim 6, the combination of Hopkins and Beaufrere disclose the moderation system of claim 5 above, where Beaufrere further discloses wherein the severity scoring mechanism considers contextual factors such as the context of interactions and the history of reported incidents associated with user IDs (Beaufrere, Paragraphs 0036-0037, 0040, score (based on user interactions) is used in order to determine what actions to be taken by the social networking system).
Regarding Claim 9, Hopkins discloses a method for detecting and moderating inappropriate behavior in a dating application (Hopkins, Paragraphs 0022-0023, online dating platforms is used as an example), comprising:
scanning messages for harmful language using NLP algorithms (Hopkins, Paragraph 0032, artificial intelligence engine determines certain undesirable qualities (e.g., hostile, extreme nervousness when speaking, etc.). Paragraphs 0062, 0067, 0076, verification service analyzes video/images in order to determine if criteria are met. Paragraph 0053, several options are provided to the user in order to communicate, including video calling, text messaging, voice-only call, etc.);
analyzing live video streams for inappropriate visual content using computer vision techniques (Hopkins, Paragraph 0032, artificial intelligence engine determines certain undesirable qualities (e.g., hostile, extreme nervousness when speaking, etc.). Paragraphs 0062, 0067, 0076, verification service analyzes video/images in order to determine if criteria are met. Paragraph 0053, several options are provided to the user in order to communicate, including video calling, text messaging, voice-only call, etc.);
enabling users to report inappropriate behavior through a user interface and tracking reported incidents associated with user IDs (Hopkins, Paragraph 0053, users are provided with an interface that can be used to report other users for inappropriate language, inappropriate conversation, or actions taken during the conversation. The system will receive and store the option(s) selected by the user and take appropriate action).
However, Hopkins fails to explicitly disclose assigning severity scores to reported incidents based on predefined criteria and patterns; and taking automated actions such as issuing warnings, suspending accounts temporarily, or permanently banning users based on severity scores.
Beaufrere, from the same or similar field of endeavor, discloses assigning severity scores to reported incidents based on predefined criteria and patterns (Beaufrere, Paragraph 0029, reporting interface allows a user to report on somebody that present hate speech, nudity, malicious activity, etc. Paragraph 0036, disabled connectivity score calculating a disabled connectivity score for a user associated with a report of malicious activity or content. When a report of malicious activity or content is received by the social networking system, the disabled connectivity scoring module computes a disabled connectivity score for a target user or a target object (e.g., the reporting user or another user or object maintained by the social networking system and associated with the report));
and taking automated actions such as issuing warnings, suspending accounts temporarily, or permanently banning users based on severity scores (Beaufrere, Paragraph 0029, based on information about the report and the reported content or action, the social networking system determines a type of action to take in response to the report).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Hopkins in view of Beaufrere in order to further modify the method of online communications from the teachings of Hopkins with the method of categorizing social networking users from the teachings of Beaufrere.
One of ordinary skill in the art would have been motivated because analyzing the activities of the user the system will be able to determine the actions of the users, whether they are malicious or not (Beaufrere – Paragraphs 0001-0003, 0012).
Regarding Claim 10, the combination of Hopkins and Beaufrere disclose the method of claim 9 above, Beaufrere further discloses further comprising:
generating detailed incident reports for human moderators to review borderline cases and make final decisions on enforcement actions (Beaufrere, Paragraphs 0018, 0042, report is manually reviewed by social networking administrators).
Regarding Claim 11, the combination of Hopkins and Beaufrere disclose the method of claim 9 above, where Hopkins further discloses wherein scanning messages for harmful language comprises utilizing sentiment analysis and keyword matching to detect toxic language, and flagging messages containing predefined keywords and phrases indicative of abusive or inappropriate behavior (Hopkins, Paragraph 0032, artificial intelligence engine determines certain undesirable qualities (e.g., hostile, extreme nervousness when speaking, etc.)).
Regarding Claim 12, the combination of Hopkins and Beaufrere disclose the method of claim 9 above, where Hopkins further discloses wherein analyzing live video streams for inappropriate visual content comprises employing object detection and gesture recognition algorithms to identify nudity, obscene gestures, and other forms of visual harassment, and flagging video interactions containing such content for review (Hopkins, Paragraph 0032, artificial intelligence engine determines certain undesirable qualities (e.g., hostile, extreme nervousness when speaking, etc.). Paragraph 0152, user can report other users for inappropriate behavior, such as nudity/sexual, underage, hate speech, spam, etc.).
Regarding Claim 13, the combination of Hopkins and Beaufrere disclose the method of claim 9 above, where Hopkins further discloses wherein assigning severity scores to reported incidents further comprises considering contextual factors such as the context of interactions and the history of reported incidents associated with user IDs to determine the appropriate severity score for each reported incident (Hopkins, Paragraph 0053, users are provided with an interface that can be used to report other users for inappropriate language, inappropriate conversation, or actions taken during the conversation. The system will receive and store the option(s) selected by the user and take appropriate action. Paragraph 0148, report user interface used to enter a report on another participant. Figs 5Q(1)-5Q(3), Paragraphs 0150-0152, user interface which includes reasons to provide the cause of the report).
Regarding Claim 14, the combination of Hopkins and Beaufrere disclose the method of claim 11 above, where Hopkins further discloses wherein the AI employed by the platform facilitates automated recommendations to users, including recommending similar users whose dates typically last approximately the same length of time as those of the user, wherein the recommendations are displayed in a dedicated "recommendations tab" within the application interface (Hopkins, Paragraph 0041, generating match recommendations. For example, activity data, such as the number of times a user is selected by other users to engage in online communications with (optionally over a specified period of time), the number of times a user has engaged with another user using a first channel of electronic communication (e.g., video call), etc.).
Regarding Claim 15, the combination of Hopkins and Beaufrere disclose the method of claim 14 above, where Hopkins further discloses wherein the AI utilizes user data and preferences to generate recommendations based on factors such as preferred date duration, common interests, geographic proximity, and language compatibility (Hopkins, Paragraphs 0043-0044, user requests to view potential matches. The system filters out users whose profiles indicate that they are not in an acceptable geographical area (e.g., are outside of the desired location specified by the requesting user), and then filter out users that do not have the desired color hair, age, height, activity data, etc.).
Regarding Claim 16, the combination of Hopkins and Beaufrere disclose the method of claim 11 above, where Hopkins further discloses wherein the AI features include a chemistry match functionality that prioritizes requests from users with similar "chemistry" to that of the user when the user assumes a role of a time-setter, wherein "chemistry" is determined based on factors including but not limited to similar date durations, shared interests, geographic proximity, and language compatibility (Hopkins, Paragraphs 0041-0044, multiple examples of how to recommend matches to a user, based on, for example, online communications with the users, number of times a user has engaged with another user, etc. Paragraph 0045, ranking and presenting to the user in a ranked order the users that match the requesting user’s criteria).
Claims 7 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Hopkins in view of Beaufrere and in further view of Russell Speight VanBlon et al (US 20180143822 A1), hereinafter “VanBlon”.
Regarding Claim 7, the combination of Hopkins and Beaufrere disclose the moderation system of claim 6 above.
However, the combination of Hopkins and Beaufrere fail to explicitly disclose further comprising: a content update mechanism, said content update mechanism comprising: a backend system configured to receive monthly content updates; and an automated deployment mechanism configured to deploy updates to the application's frontend UI, including new virtual backgrounds, interactive games, and additional features to enhance user interaction.
Beaufrere, from the same or similar field of endeavor, discloses further comprising: a content update mechanism, said content update mechanism comprising:
a backend system configured to receive monthly content updates (VanBlon, Paragraph 0044, application receiving updates at different intervals, including monthly updates);
and an automated deployment mechanism configured to deploy updates to the application's frontend UI, including new virtual backgrounds, interactive games, and additional features to enhance user interaction (VanBlon, Paragraph 0044, monthly updates include updates to features of the application).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Hopkins in view of Beaufrere and in further view of VanBlon in order to further modify the method of online communications from the teachings of Hopkins and the method of categorizing social networking users from the teachings of Beaufrere with the method of intelligently controlling application updates of applications installed on an electronic device from the teachings of VanBlon.
One of ordinary skill in the art would have been motivated because determining when to download an update to an application the device will have a better performance (VanBlon – Paragraphs 0002-0010, 0044).
Regarding Claim 8, the combination of Hopkins, Beaufrere, and VanBlon disclose the moderation system of claim 7 above, where VanBlon further discloses wherein updates are deployed automatically to ensure all users receive the latest features without manual intervention (VanBlon, Paragraph 0072, enabling automatic updates based on application update policy).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. All the references listed on 892 are related to the subject matter of matching users in an online social networking system.
Some of the prior art include:
US 10321284 B1, US 20190065609 A1, and US 20230118533 A1.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAVIER O GUZMAN whose telephone number is (571)270-0588. The examiner can normally be reached Monday - Friday 8 am to 4 pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Brian J Gillis can be reached at 571-272-7952. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAVIER O GUZMAN/ Primary Examiner, Art Unit 2446