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 . Claim 1 are presented for examination.
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 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.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 01/16/2025. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Provisional Priority
This present application (18/779640) appears to claim a continuation of U.S. Patent Application No. 17/900,866, filed August 31, 2022, which is a continuation-in-part of U.S. Patent Application 17/393,540, filed August 4, 2021, now U.S. Patent No. 11,706,176, issued July 18, 2023, which is a continuation of U.S. Patent Application No. 16/372,140, filed April 1, 2019, now U.S. Patent No. 11,095,585, issued August 17, 2021, which is a continuation of U.S. Patent Application No. 15/187,674, filed June 20, 2016, now U.S. Patent No. 10,250,538, issued April 2, 2019, which is a continuation-in-part of U.S. Patent Application No. 14/738,874, filed June 13, 2015, now U.S. Patent No. 9,686,217, issued June 20, 2017, which claims the benefit of U.S. Provisional Patent Application No. 62/012,296, filed June 14, 2014.
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) to the originally filed provisional application 62/012296 is not granted because the subject matter is broader and completely different in scope and has totally distinct utility. For example, the first US patent 9686217 is directed to messaging application stopping cyber bullying by employing re-thinking techniques that generate an alert a message on a smart phone prior to sending of the hurtfully or bullying message to another user. Whereas the current application is directed machine learning model techniques not the original ReThink concepts.
Applicant is requested to perfect the effective filing date and properly reflect it in the paragraph [001] of the specification. Currently as best understood the effective filling date of the current applicant can be reasonably extended to the its parent application 17/900866 filed on 08/31/2022.
Internet Communication Authorization
The examiner recommends filling a written authorization for internet communication in response to the present action. Doing so permits the USPTO to communicate with applicant using internet email to schedule interviews or discuss other aspects of the application. Without a written authorization in place, the USPTO cannot respond to Internet correspondence received from Applicant. The preferred method of providing authorization is by filing form PTO/SB/439, available at: https://www.uspto.gov/patent/forms/forms. See MPEP § 502.03 for other methods of providing written authorization.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement.
Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
The USPTO internet Web site contains terminal disclaimer forms which may be used. Please visit http://www.uspto.gov/forms/. The filing date of the application will determine what form should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements are auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-18 of US patent 12341739. Although the conflicting claims are not identical, they are not patentably distinct from each other because claims 20-49 are anticipated by claims 1-18 of the issued US patent application.
Instant Application:
Claims: 1
Issued US pat: 12341739
Claims: 1
1 A method for identifying offensive message content comprising: 1. for each particular responsive message of a plurality of responsive messages received in response to an initial message:
providing, by one or more computers, content of the particular responsive message as an input to a machine learning model that has been trained to predict a likelihood that an initial message provided by a first user device includes offensive content based on processing of responsive message content from a different user device provided in response to the initial message;
processing, by the one or more computers, the content of the particular responsive message through the machine learning model to generate output data indicating a likelihood that the initial message includes offensive content; and
storing, by the one or more computers, the generated output data;
determining, by the one or more computers and based on the output data generated for each of the plurality of responsive messages, whether the initial message likely includes offensive content; and
based on a determination, by the one or more computers, that the output data generated for each of the plurality of responsive messages indicates that the initial message likely includes offensive content, performing, by one or more computers, a remedial operation to mitigate exposure to the offensive content
A method for identifying offensive message content comprising:
for each particular responsive message of a plurality of responsive messages received in response to an initial message:
providing, by one or more computers, content of the particular responsive message as an input to a machine learning model that has been trained to predict a likelihood that an initial message provided by a first user device includes offensive content based on processing of responsive message content from a different user device provided in response to the initial message;
processing, by one or more computers, the content of the particular responsive message through the machine learning model to generate output data indicating a likelihood that the initial message includes offensive content; and
storing, by one or more computers, the generated output data;
determining, by one or more computers and based on the output data generated for each of the plurality of responsive messages, whether the initial message likely includes offensive content; and
based on a determination, by one or more computers, that the output data generated for each of the plurality of responsive messages indicates that the initial message likely includes offensive content, performing, by one or more computers, one or more remedial operations to mitigate exposure to the offensive content, wherein performing the one or more remedial operations comprises: adjusting, using one or more computers, a content score associated with the initial message content, wherein the adjusted content scores causes the initial message content to be demoted in list of content items.
Claim 1 is rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1 of U.S. Patent application 17/900,866 identified by US patent 12341739. Claim 1 of instant application is analogous to the issue the issued application. Claims 1 of the instant application are contained in most of the elements of claim 1 in the earlier issued US patent 12341739 and thus anticipate claim 1 of the instant application. This is a non-provisional obviousness-type double patenting.
This is substantially similar in nature to this application as can clearly be seen. Although, the conflicting claims are not identical, they are not patentably distinct from each other because the subject matter claimed in the instant application is substantially similar in nature of US patent 12341739. This is a non-statutory obviousness-type double patenting rejection.
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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.
Claim 1 are rejected under 35 U.S.C. 103 as being unpatentable over in view of Anders et al (US pub, 2020/0065417 A1) in view of Pavlopoulos et al (ACL 2020).
Referring to claim 1, Anders teaches a method for identifying offensive message content ([abs], ¶[001], [006], [019] expressly discloses identifying toxic/offensive social media content and mitigating its effect) comprising:
for each particular responsive message of a plurality of responsive messages received in response to an initial message (Anders analyze multiple social media messages within interactions threads, groups, or conversations including replies and ongoing exchanges see para [004], [0018], [0026], [0034]):
providing, by one or more computers, content of the particular responsive message as an input from a different user device provided in response to the initial message (see ¶ [024]-[027], [068]-[069], Anders feeds each social media message into topic analysis, sentiment analysis, emotion analysis and velocity analysis modules which collective functions as a ML-based classifier);
processing, by the one or more computers, the content of the particular responsive message through the machine learning model to generate output data indicating a likelihood that the initial message includes offensive content (Anders ¶ [025], [032], [082], [083], computes toxicity scores, sentiment scores and class probabilities~liklihoods for each analyzed message); and
storing, by the one or more computers, the generated output data (Anders [033], [034], [038], stores toxicity scores, class assignments, trends, and historical message data to enable forecasting and ongoing model updates);
determining, by the one or more computers and based on the output data generated for each of the plurality of responsive messages, whether the initial message likely includes offensive content (see ¶ [034], [085]-[087] forecasts toxicity trends using multiple messages scores classes, timing and rates of change - determination is based on aggregated outputs from plural messages ); and
based on a determination, by the one or more computers, that the output data generated for each of the plurality of responsive messages indicates that the initial message likely includes offensive content, performing, by one or more computers, a remedial operation to mitigate exposure to the offensive content (see ¶[035]-[037], [038], [085], [086], Anders applies remedial measures when toxicity trend increases to include warnings, blocking or throttling posting, content restriction, moderation or bans).
Anders teaches toxicity scoring, aggregation across messages and remedial action but expressly lacks a machine learning model that has been trained to predict a likelihood that an initial message provided by a first user device includes offensive content based on processing of responsive message content.
However Pavlopoulos teaches machine learning classifier that determines whether a target comment/message is toxic and focuses on inferring properties of a specific target message. Furthermore, Pavlopoulos teaches a machine learning model that has been trained to predict a likelihood that an initial message provided by a first user device includes offensive content based on processing of responsive message content (Table 1,2 RQ1/RQ2, Fig. 3-5; Pavlopoulos explicitly identifies a Target message whose toxicity is inferred and teaches training ML classifiers to output a toxicity probability for that target message using responsive message as context)
It would have been obvious to one of ordinary skill in the art to combine Anders’ multi-message toxicity aggregation and remedial framework with Pavlopoulos’ ML models trained to infer the offensiveness of a specific target message using individually processed responsive messages, because both references address the same problem—accurate detection and mitigation of offensive content—and Pavlopoulos teaches a known technique (context-conditioned ML inference for a target message) that predictably improves Anders’ system by supplying the specific directionality (responses → target message) and per-response processing. Without teaching away, the combination applies known contextual toxicity techniques to known moderation systems to achieve expected results.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Additional relevant prior art can be found in the included form PTO-892 (Notice of Cited References).
Applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the references cited or the objections made. He or she must also show how the amendments avoid such references or objections See 37 CFR 1.111 (c).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AFTAB N. KHAN whose telephone number is (571)270-5172. The examiner can normally be reached on Monday-Friday 8AM-5PM EST. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Glenton Burgess can be reached on 571-272-3949. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/AFTAB N. KHAN/
Primary Examiner, Art Unit 2454