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 .
Claims 1-4, 6-11, 13-17, and 19-23. Claims 1, 8, and 15 are independent.
Response to Amendment
The office action is responsive to the amendments filed on 07/15/2026. As
directed by the amendments claims 1-4, 6-11, 13, 15-17, and 19 are amended. Claims 5, 12, and 18 are canceled. Claims 21-23 are new.
Response to Arguments
Applicant's arguments filed 07/15/2026 have been fully considered but they are not fully persuasive.
Applicant arguments regarding 35 U.S.C. § 101:
Examiner response: Examiner respectfully disagrees, the amended limitations for generating first data, generating second data, clustering, and classifying are all reciting mental processes performed by high level models or generic computer elements. Claims 1, 8, and 15, as amended, recite an ordered combination of limitations describing mental steps under step 2A Prong 1, and additional elements under steps 2A Prong 2 & 2B as detailed in the updated 101 rejection below. The additional elements as disclosed alone or in combination do not integrate the judicial exception into practical application as they are insignificant extra solution activity in combination of generic computer functions that are implemented to perform the disclosed abstract idea. The additional elements as disclosed in combination of the abstract idea are not sufficient to amount to significantly more than the judicial exception as they are well, understood, routine and conventional activity as disclosed in combination of generic computer functions that are implemented to perform the disclosed abstract idea.
MPEP §2106.05(a) reads:
During examination, the examiner should analyze the "improvements" consideration by evaluating the specification and the claims to ensure that a technical explanation of the asserted improvement is present in the specification, and that the claim reflects the asserted improvement.
However, the MPEP (§2106.05(a)(II)) also warns, “it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology.” Here, the alleged improvement in the form of classifying reports which is an improvement to the abstract idea of classifying data. Applicants claimed improvement is describing an improvement to an abstract idea and not to an improvement to a computer or technical field. MPEP 2106.05(a) says an improvement in the abstract idea itself is not an improvement in technology.
Applicant arguments regarding 35 U.S.C. § 103:
Examiner response: Applicant’s arguments, filed 07/15/2026, with respect to the 35 U.S.C. § 103 rejection have been fully considered and are persuasive. The 35 U.S.C. § 103 rejection of has been withdrawn.
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 1-4, 6-11, 13-17, and 19-23 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
According to the first part of the analysis, in the instant case, claims 1-4, 6-7, and 21-22 are directed to a method, claims 8-11, 13-14, and 23 are directed to a system, and claims 15-17, and 19-20 is directed to a non-transitory computer-readable medium. Thus, each of the claims falls within one of the four statutory categories (i.e., process, machine, manufacture, or composition of matter).
Regarding Claim 1:
2A Prong 1:
generating, (This step for generating a first data set is practically performable in the human mind and is understood to be a recitation of a mental process (i.e., evaluation).)
generating one or more second data sets for a plurality of prior user reports based on a plurality of word-level vector embeddings, wherein the plurality of word-level vector embeddings is based on respective sets of keywords and respective summaries corresponding to the plurality of prior user reports; (This step for generating a second data set is practically performable in the human mind and is understood to be a recitation of a mental process (i.e., evaluation).)
clustering, by an unsupervised machine learning clustering classifier and based on the one or more second data sets, prior report statements from the plurality of prior user reports into a plurality of clusters; (This step for clustering prior report statements is practically performable in the human mind and is understood to be a recitation of a mental process with the aid of pen and paper (i.e., evaluation).)
classifying, (This step for classifying user reports is practically performable in the human mind and is understood to be a recitation of a mental process (i.e., judgment/evaluation).)
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
A computer-implemented method for managing user reports, comprising:
by at least one computer processor (The computer-implemented method comprising processor is understood to be generic computer elements – See MPEP 2106.05(f).)
generating, by a language model, a set of data agents corresponding to the plurality of clusters, wherein each data agent of the set of data agents corresponds to a respective cluster of the plurality of clusters and includes a description generated by the language model based on prior report statements in the respective cluster; (This is adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
providing the set of data agents to a supervised machine learning classifier; (This step is directed to transmitting or receiving information, which is understood to be insignificant extra-solution activity and data gathering. See MPEP 2106.05(g).)
by the supervised machine learning classifier (This step is adding the words “apply it” (or an equivalent) with the judicial exception, or merely applying a machine learning as a tool to perform the abstract idea (e.g., generate labels) - see MPEP 2106.05(f).)
storing the user report in a database managed by the selected data agent. (Theis step id directed to storing information, is understood to be insignificant extra- solution activity and data gathering. See MPEP 2106.05(g).)
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are insignificant extra solution activity in combination of generic computer functions that are implemented to perform the disclosed abstract idea above.
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
A computer-implemented method for managing user reports, comprising:
by at least one computer processor (The computer-implemented method comprising processor is understood to be generic computer elements – See MPEP 2106.05(f).)
generating, by a language model, a set of data agents corresponding to the plurality of clusters, wherein each data agent of the set of data agents corresponds to a respective cluster of the plurality of clusters and includes a description generated by the language model based on prior report statements in the respective cluster; (This is adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
providing the set of data agents to a supervised machine learning classifier; (This step is directed to transmitting or receiving information, which is understood to be insignificant extra-solution activity and is well understood, routine and conventional activity of transmitting and receiving data as identified by the court (MPEP2106.05(d)(ll)(i))))
by the supervised machine learning classifier (This step is adding the words “apply it” (or an equivalent) with the judicial exception, or merely applying a machine learning as a tool to perform the abstract idea (e.g., generate labels) - see MPEP 2106.05(f).)
storing the user report in a database managed by the selected data agent. (This step is directed to storing information, which is understood to be insignificant extra-solution activity and is well understood, routine and conventional activity as identified by the court (MPEP 2106.05(d)(ll)(IV)))));
The additional elements as disclosed above in combination of the abstract idea
are not sufficient to amount to significantly more than the judicial exception as they are
well, understood, routine and conventional activity as disclosed in combination
of generic computer functions that are implemented to perform the disclosed abstract idea above.
Regarding Claim 8: see the rejection of claim 1 above. Same rationale applies.
2A Prong 2 & 2B: The claim recites another additional element “A system, comprising: one or more memories configured to store a plurality of prior user reports including multiple prior report statements; and at least one processor coupled to the one or more memories and configured to perform operations comprising:” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
Regarding Claim 15: see the rejection of claim 1 above. Same rationale applies.
2A Prong 2 & 2B: The claim recites another additional element “A non-transitory computer-readable medium having instructions stored thereon that, when executed by at least a computing device, cause the computing device to perform operations comprising:” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
Regarding Claims 2, and 9
2A Prong 1: The claim does not recite an Abstract idea.
2A Prong 2 & 2B:
wherein the selected data agent includes a description of the user report stored in the database (The specification of data to be stored is understood to be a field of use limitation. The limitation further specifies the data agent- See MPEP 2106.05(h).)
Regarding Claims 3 and 10
2A Prong 1: The claim does not recite an Abstract idea.
2A Prong 2 & 2B:
the language model includes a probabilistic language model or a neural network-based language model. (The specification of data to be stored is understood to be a field of use limitation. The limitation further specifies the language model - See MPEP 2106.05(h).)
Regarding Claims 4, 11, and 17
2A Prong 1:
determining, by the supervised machine learning classifier, that the user query corresponds to a second data agent including a second description of user reports stored in a second database. (This step is practically performable in the human mind and is understood to be a recitation of a mental process (i.e., judgment/evaluation).)
2A Prong 2:
wherein the selected data agent is a first data agent, and the method further comprises: receiving a user query; (This step is directed to transmitting or receiving information, which is understood to be insignificant extra-solution activity and data gathering. See MPEP 2106.05(g).)
2B:
wherein the selected data agent is a first data agent, and the method further comprises: receiving a user query; (This step is directed to transmitting or receiving information, which is understood to be insignificant extra-solution activity and is well understood, routine and conventional activity of transmitting and receiving data as identified by the court (MPEP2106.05(d)(ll)(i))))
Regarding Claim 6
2A Prong 1: The claim does not recite an Abstract idea.
2A Prong 2 & 2B:
wherein the plurality of word-level embeddings further include truncated embeddings to reduce a dimensionality of the plurality of word-level embeddings to generate the one or more second data sets. (The specification of data to be stored is understood to be a field of use limitation. The limitation further specifies the word embedding - See MPEP 2106.05(h).)
Regarding Claim 7
2A Prong 1: The claim does not recite an Abstract idea.
2A Prong 2 & 2B:
wherein the plurality of sentence-level embeddings include SentenceBERT- based embeddings, Universal Sentence Encoder-based embeddings, or FastText-based embeddings; (The specification of data to be stored is understood to be a field of use limitation. The limitation further specifies the word embedding - See MPEP 2106.05(h).)
Regarding Claims 13, 19, and 21
2A Prong 1: The claim does not recite an Abstract idea.
2A Prong 2 & 2B:
wherein the supervised machine learning classifier includes a supervised neutral network, a support vector machine (SVM) classifier, a random forest classifier, or a K nearest neighbors supervised machine learning classifier. (The specification of data to be stored is understood to be a field of use limitation. The limitation further specifies the supervised machine learning classifier - See MPEP 2106.05(h).)
Regarding Claims 14, 20, and 22
2A Prong 1: The claim does not recite an Abstract idea.
2A Prong 2 & 2B:
wherein the unsupervised machine learning clustering classifier includes an Ordering Points To Identify the Clustering Structure (OPTICS) algorithm, a density-based cluster ordering algorithm, or a Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. (The specification of data to be stored is understood to be a field of use limitation. The limitation further specifies the unsupervised machine learning clustering classifier - See MPEP 2106.05(h).)
Regarding Claim 16
2A Prong 1: The claim does not recite an Abstract idea.
2A Prong 2 & 2B:
wherein the selected data agent includes a description of the user report stored (The specification of data to be stored is understood to be a field of use limitation. The limitation further specifies the selected data agent - See MPEP 2106.05(h).), and wherein the language model includes a probabilistic language model or a neural network-based language model. (The specification of data to be stored is understood to be a field of use limitation. The limitation further specifies the language model - See MPEP 2106.05(h).)
Regarding Claim 23
2A Prong 1:
wherein the first data set is generated by sentence embedding of the list of keywords and the summary of the user report, (This step is practically performable in the human mind and is understood to be a recitation of a mental process (i.e., judgment/evaluation).)
2A Prong 2 & 2B:
and wherein the plurality of sentence-level embeddings include SentenceBERT-based embeddings, Universal Sentence Encoder-based embeddings, or FastText-based embeddings. (The specification of data to be stored is understood to be a field of use limitation. The limitation further specifies the word embedding - See MPEP 2106.05(h).)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Backas et al. (US 2021/0019648 A1) describes clustering and labeling user reports.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TEWODROS E MENGISTU whose telephone number is (571)270-7714. The examiner can normally be reached Mon-Fri 9:30-5:30.
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, ABDULLAH KAWSAR can be reached at (571)270-3169. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TEWODROS E MENGISTU/Primary Examiner, Art Unit 2127
