DETAILED ACTION
Remarks
The instant application having Application Number 18/545,072 filed on December 19, 2023 has a total of 20 claims pending in the application; there are 3 independent claims and 17 dependent claims, all of which are presented for examination by the examiner.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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.
Examiner Notes
Examiner cites particular columns and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
The examiner requests, in response to this Office action, supports are shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line no(s) in the specification and/or drawing figure(s). This will assist the examiner in prosecuting the application.
When responding to this office action, 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).
Information Disclosure Statement
As required by M.P.E.P. 609(C), the applicant’s submissions of the Information Disclosure Statements dated December 19, 2023 is acknowledged by the examiner and the cited references have been considered in the examination of the claims now pending. As required by M.P.E.P 609 C (2), a copy of the PTOL-1449 initialed and dated by the examiner is attached to the instant office action.
Drawings
The applicant’s drawings submitted are acceptable for examination purposes.
CLAIM INTERPRETATION
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
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 16-17 and 19-20 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 pre-AIA the applicant regards as the invention.
Claim limitations “a training component”, “a pseudo-sample generator”, “a text encoder”, “a social media application” recited in claims 16-17 and 19-20 respectively invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim 13 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 pre-AIA the applicant regards as the invention. Claim 13 is vague and indefinite because the phrase "moderation action" has not been clearly defined in the claim. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir.1993). Therefore, one of ordinary skill in the art would not be able to ascertain the metes and bounds of the claimed invention. Applicants need not confine themselves to the terminology used in the prior art, but are required to make clear and precise the terms that are used to define the invention whereby the metes and bounds of the claimed invention can be ascertained. See MPEP 2173.05(a)(I). Appropriate correction is required.
The Examiner has given the phrase "moderation action" its broadest reasonable interpretation. For examination purposes, all claim interpretation is predicated upon the broadest reasonable interpretation of the claim terms which would be fairly conveyed to one of ordinary skill in the pertinent art.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding independent Claims 1, 10, and 15:
Step 1 Analysis:
Claims 1 and 10 recites “A method…”, the claim recites a series of steps and therefore is process.
Claim 15 recites “An apparatus …”; therefore, the claim is a machine.
Step 2A Prong One Analysis: The claim, under the broadest reasonable interpretation, recites limitations directed to an abstract idea, including mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion), but for the recitation of mere instructions to apply an exception language. In particular, the following limitations are directed to an abstract idea:
obtaining a training sample comprising a text graph and a label indicating whether the text graph includes misinformation;
generating a pseudo-sample by modifying the text graph to obtain a modified text graph, wherein the pseudo-sample includes the modified text graph and the label; and
training a graph classifier to identify misinformation using the training sample and the pseudo-sample.
This limitation is a process that, under their broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting “processor” and “memory”, nothing in the claim element precludes the steps from practically being performed in a human mind or with the aid of pen and paper. For example, the “obtaining”, “generating” and “training” in the context of this claim encompasses a user mentally, and with the aid of pen and paper writing the changes down on a sheet of paper and examine the list to determine the relevant ones. For example, a human being can obtain information/data analyze information/data and generate sample information/data and can find misinformation.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A - Prong Two: Integrated into a Practical Application
The judicial exception is not integrated into a practical application. In particular, the additional steps: the “obtaining”, “generating” and “training” steps mount to data gathering which are considered to be insignificant extra-solution activity (see MPEP 2106.05(g)), and the “training” and “generating” steps are considered as a mere instruction to apply an exception to perform an existing process on a generic computer and/or no more than an idea of a solution or outcome on a generic computer (see MPEP 2106.05(f)). Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea, thus fail to integrate the abstract idea into a practical application. See MPEP 2106.05(g).
Step 2B: Claim provides an Inventive Concept
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The insignificant extra-solution activities identified above, which include the data-gathering and the step of “obtaining”, “generating” and “training” are recognized by the courts as well-understood, routine, and conventional activities when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d)(II)). For these reasons, there is no inventive concept in the claim, and thus it is ineligible.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application.
Independent claims 10 and 15 have the similar limitations as claim 1 and are rejected for at least the same reasons as claim 1.
Regarding claim 2. The method of claim 1, wherein: the text graph includes a root node and the label indicates whether the root node includes misinformation.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 3. The method of claim 1, further comprising: obtaining an unlabeled sample including an additional text graph; generating a pseudo-label for the unlabeled sample using the graph classifier to obtain a predicted pseudo-sample including the unlabeled sample and the pseudo-label; and performing additional training of the graph classifier based on the predicted pseudo-sample.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 4. The method of claim 1, wherein: the text graph includes a plurality of text nodes and at least one edge connecting at least two of the plurality of text nodes.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 5. The method of claim 4, wherein modifying the text graph comprises: adding an additional text node or an additional edge.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 6. The method of claim 4, wherein modifying the text graph comprises: removing at least one of the plurality of text nodes or the at least one edge.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 7. The method of claim 4, wherein modifying the text graph comprises: modifying at least one of the plurality of text nodes.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 8. The method of claim 4, further comprising: computing a node embedding for each of the plurality of text nodes, wherein the graph classifier takes the node embedding as input.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 9. The method of claim 1, wherein training the graph classifier comprises: generating a predicted label for the text graph; and computing a loss function based on the label and the predicted label.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 10. A method for identifying misinformation, comprising: obtaining a text graph; generating a label for the text graph using a graph classifier, wherein the graph classifier is trained to identify misinformation based on a pseudo-sample obtained by modifying a graph structure of a training sample; and identifying misinformation in the text graph based on the label.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 11. The method of claim 10, wherein: the text graph includes a plurality of text nodes and at least one edge connecting at least two of the plurality of text nodes.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 12. The method of claim 10, wherein: the text graph comprises a social media post.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 13. The method of claim 12, further comprising: performing a moderation action based on identifying misinformation in the text graph.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 14. The method of claim 12, wherein: the text graph includes a response to the social media post.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 16. The apparatus of claim 15, further comprising: a training component configured to train the graph classifier.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 17. The apparatus of claim 15, further comprising: a pseudo-sample generator configured to generate the pseudo-sample.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 18. The apparatus of claim 17, wherein: the pseudo-sample generator comprises a language generation model.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 19. The apparatus of claim 15, further comprising: a text encoder configured to compute a node embedding for the training sample.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
Regarding claim 20. The apparatus of claim 15, further comprising: a social media application configured to perform a moderation action based on identifying misinformation.
The judicial exception is not integrated into a practical application. In particular, this additional limitation mounts to data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)), and does not amount to significantly more than the above-identified judicial exception.
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 of this title, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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 1-3, 9-10 and 12-15 are rejected under 35 U.S.C. 103 as being unpatentable over Bronstein (US Patent Publication No. 2021/0049441 A1) in view of Li et al. (Chinese Patent Publication No. CN 114840663 A, ‘Li’, hereafter).
Regarding claim 1. Bronstein teaches a method for identifying misinformation (Bronstein [0018]), comprising:
obtaining a training sample comprising a text graph and a label indicating whether the text graph includes misinformation (Bronstein [0136]); and
training a graph classifier to identify misinformation using the training sample and the pseudo-sample (Bronstein [0035-0038], [0096], [0136]).
Bronstein does not teach
generating a pseudo-sample by modifying the text graph to obtain a modified text graph, wherein the pseudo-sample includes the modified text graph and the label;
However, Li teaches
generating a pseudo-sample by modifying the text graph to obtain a modified text graph, wherein the pseudo-sample includes the modified text graph and the label (Li, page 4, line 56 – page 5, line 1);
Therefore, it would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention was made having the teachings of Bronstein and Li before him/her, to modify Bronstein with the teaching of Li’s model training method and device, text classification method, electronic equipment and storage medium. One would have been motivated to do so for the benefit of provide a model training method and apparatus, a text classification method, an electronic device, and a storage medium, so as to solve the defects of low efficiency and low accuracy in classifying news texts in the prior art (Li, page 2, lines 31-33).
Regarding claim 2. Bronstein as modified teaches, wherein: the text graph includes a root node and the label indicates whether the root node includes misinformation (Bronstein [0067-0070], [0053]).
Regarding claim 3. Bronstein as modified teaches, further comprising:
obtaining an unlabeled sample including an additional text graph (Li, page 5, lines 2-16);
generating a pseudo-label for the unlabeled sample using the graph classifier to obtain a predicted pseudo-sample including the unlabeled sample and the pseudo-label (Li, page 3, lines 13-23, 39-51, page 5, lines 1-16); and
performing additional training of the graph classifier based on the predicted pseudo-sample (Li, page 3, lines 25-26, 39-51).
Regarding claim 9. Bronstein as modified teaches, wherein training the graph classifier comprises: generating a predicted label for the text graph; and computing a loss function based on the label and the predicted label (Bronstein [0284]).
Regarding claim 10, although claim 10 directed to a method, it is similar in scope to claim 1. The method steps of claim 1 substantially encompass the method recited in claim 10. Therefore; claim 10 is rejected for at least the same reason as claim 1 above.
Regarding claim 12. Bronstein as modified teaches, wherein: the text graph comprises a social media post (Bronstein [0016-0018], [0048]).
Regarding claim 13. Bronstein as modified teaches, further comprising: performing a moderation action based on identifying misinformation in the text graph (Bronstein [0096], [0268]).
Regarding claim 14. Bronstein as modified teaches, wherein: the text graph includes a response to the social media post (Bronstein [0046], [0048]).
Regarding claim 15. Bronstein teaches an apparatus for identifying misinformation (Bronstein [0016], [0018]), comprising:
a graph classifier comprising parameters stored in the at least one memory component, the graph classifier trained to identify misinformation based on a pseudo-sample obtained by modifying a graph structure of a training sample (Bronstein [0035-0038], [0096], [0136]).
Bronstein does not teach
at least one memory component; at least one processor configured to execute instructions stored in the at least one memory component;
However, Li teaches
at least one memory component; at least one processor configured to execute instructions stored in the at least one memory component (Li, page 3, lines 32-37, page 14, lines 30-38);
Therefore, it would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention was made having the teachings of Bronstein and Li before him/her, to modify Bronstein with the teaching of Li’s model training method and device, text classification method, electronic equipment and storage medium. One would have been motivated to do so for the benefit of provide a model training method and apparatus, a text classification method, an electronic device, and a storage medium, so as to solve the defects of low efficiency and low accuracy in classifying news texts in the prior art (Li, page 2, lines 31-33).
Claims 4, 5, 7, 8 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Bronstein (US Patent Publication No. 2021/0049441 A1) in view of Li et al. (Chinese Patent Publication No. CN 114840663 A, ‘Li’, hereafter) and further in view of Zhang et al. (US Patent Publication No. CN 114840663 A, ‘Zhang’, hereafter).
Regarding claim 4. Bronstein and Li do not teach, wherein: the text graph includes a plurality of text nodes and at least one edge connecting at least two of the plurality of text nodes.
However, Zhang teaches wherein: the text graph includes a plurality of text nodes and at least one edge connecting at least two of the plurality of text nodes (Zhang [0004-0005] & Fig. 4).
Therefore, it would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention was made having the teachings of Bronstein, Li and Zhang before him/her, to further modify Bronstein with the teaching of Zhang’s graph based cross-lingual zero-shot transfer. One would have been motivated to do so for the benefit of handling question-answering tasks using a cross-language model (Zhang, Abstract, [0002]).
Regarding claim 5. Bronstein as modified teaches, wherein modifying the text graph comprises: adding an additional text node or an additional edge (Zhang [0028]).
Regarding claim 7. Bronstein as modified teaches, wherein modifying the text graph comprises: modifying at least one of the plurality of text nodes (Zhang [0022]).
Regarding claim 8. Bronstein as modified teaches, further comprising: computing a node embedding for each of the plurality of text nodes, wherein the graph classifier takes the node embedding as input (Zhang [0076-0077]).
Regarding claim 11. Bronstein as modified teaches, wherein: the text graph includes a plurality of text nodes and at least one edge connecting at least two of the plurality of text nodes (Zhang [0004-0005] & Fig. 4).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Bronstein (US Patent Publication No. 2021/0049441 A1) in view of Li et al. (Chinese Patent Publication No. CN 114840663 A, ‘Li’, hereafter) in view of Zhang et al. (US Patent Publication No. CN 114840663 A, ‘Zhang’, hereafter) and further in view of Tran et al. (US Patent Publication No. 2021/0157872 A1, ‘Tran’, hereafter).
Regarding claim 6. Bronstein, Li and Zhang do not teach, wherein modifying the text graph comprises: removing at least one of the plurality of text nodes or the at least one edge.
However, Tran teaches wherein modifying the text graph comprises: removing at least one of the plurality of text nodes or the at least one edge (Tran [0037], [0039], [0103]).
Therefore, it would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention was made having the teachings of Bronstein, Li, Zhang and Tran before him/her, to further modify Bronstein with the teaching of Tran’s natural language processing using a conditional graph modification technique. conventional NLP devices are unable to modify an existing structured representation based on a natural language modification command. Therefore, it would have been motivated to do so for the benefit of changing structured representations (Tran, Abstract, [0003]).
Claims 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bronstein (US Patent Publication No. 2021/0049441 A1) in view of Li et al. (Chinese Patent Publication No. CN 114840663 A, ‘Li’, hereafter) and further in view of David (US Patent Publication No. 2021/0157872 A1).
Regarding claim 16. Bronstein and Li do not teach, further comprising: a training component configured to train the graph classifier.
However, David teaches further comprising: a training component configured to train the graph classifier (David [0080], [0090]).
Therefore, it would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention was made having the teachings of Bronstein, Li and David before him/her, to further modify Bronstein with the teaching of David’s method, system, and product for filtering out unwanted social media content in real-time. One would have been motivated to do so for the benefit of filtering out any unwanted content comprising but not limited to harassment, threat, abuse, sexual aggression, religious aggression, fake news, and fake videos prior to viewing by recipients and to automate reporting (David, Abstract, [0002]).
Regarding claim 17. Bronstein as modified teaches, further comprising: a pseudo-sample generator configured to generate the pseudo-sample (Bronstein [0156], [0266], [0278]).
Regarding claim 18. Bronstein as modified teaches, wherein: the pseudo-sample generator comprises a language generation model (David [0048], [0080-0081], [0113]).
Regarding claim 19. Bronstein as modified teaches, further comprising: a text encoder configured to compute a node embedding for the training sample (David [0126-0129]).
Regarding claim 20. Bronstein as modified teaches, further comprising: a social media application configured to perform a moderation action based on identifying misinformation (Bronstein [0037-0039]).
Conclusion
The prior art made of record, listed on form PTO-892, and not relied upon, if any, is considered pertinent to applicant’s disclosure.
Galle et al. (US Patent Publication No. 2023/0109734 A1) discloses a computer-implemented method for detecting machine-generated documents in a collection of documents including machine-generated and human-authored documents. The computer-implemented method includes computing a set of long-repeated substrings (such as super-maximal repeats) with respect to the collection of documents and using a subset of the long-repeated substrings to designate documents containing the subset of the repeated substrings as machine-generated. The documents designated as machine-generated serve as positive examples of machine-generated documents and a set of documents including at least one human-authored document serves as negative examples of machine-generated documents. A plurality of classifiers are trained with a dataset including both the positive and negative examples of machine-generated documents. Classified output of the classifiers is then used to detect an extent to which a given document of the dataset is machine-generated.
Linck et al. (US Patent Publication No. 20220269938 A1) discloses to reduce misinformation consumption in the media, a computer-implemented method is described for presenting thought-provoking information about a media product that includes receiving media consumption data indicating a media product was consumed via a computing device user interface; determining claims for the media product; identifying a plurality of related media products based at least on a topic of the media product; determining positions for the plurality of related media products with respect to the one or more claims; determining a most contested claim as a claim that satisfies a condition corresponding to having a predetermined number of disagreeing related media products; generating a question based on the most contested claim and a paragraph including the most contested claim; generating an answer to the question based on the question and the related media product that disagrees with the most contested claim; and presenting the question and answer via the user interface.
Ameri (US Patent Publication No. 20210073654 A1) discloses and optimized, human-centered personalized search service where content is fully classified by community interests, experts by just in time learning, problem solving and digital assistants. This Knowledge Currency method has the capacity to acquire, organize, store, rank, and filter knowledge about facts and relationships. The knowledge refinery process is broken down into stages that can be parallel workflow leveraging a multi-step content topic extraction and refinery process for personalized searches with domain knowledge experts to connect collaboratively as well as knowledge reliability ranking score for element nodes on a knowledge graph.
Wu et al. (US Patent Publication No. 2021/0209139 A1) discloses a passage text and a corresponding answer text, perform a word-level soft alignment to obtain contextualized passage embeddings and contextualized answer embeddings, and a hidden level soft alignment on the contextualized passage embeddings and the contextualized answer embeddings to obtain a passage embedding matrix. Construct a passage graph of the passage text based on the passage embedding matrix, and apply a bidirectional gated graph neural network to the passage graph until a final state embedding is determined, during which intermediate node embeddings are fused from both incoming and outgoing edges. Obtain a graph-level embedding from the final state embedding, and decode the final state embedding to generate an output sequence word-by-word. Train a machine learning model to generate at least one question corresponding to the passage text and the answer text, by evaluating the output sequence with a hybrid evaluator combining cross-entropy evaluation and reinforcement learning evaluation.
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/HASANUL MOBIN/
Primary Examiner, Art Unit 2168
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