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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on August 27, 2026, has been entered.
Status of the Claims
Claims 1, 5-11, and 15-22 were previously pending and subject to a final rejection dated June 2, 2026. In the RCE, submitted on August 27, 2026, claims 1, 7-8, 11, 17-18, and 22 were amended, and claims 9, 19, and 21 were cancelled. Therefore, claims 1, 5-8, 10-11, 15-18, 20 and 22 are currently pending and subject to the non-final rejection below.
Response to Arguments
Applicants Remarks on Page 9 of the RCE, regarding the previous claim objections have been fully considered and are found persuasive in view of the amended claims.
Applicants Remarks on Page 9 of the RCE, regarding the previous claim rejections under 35 U.S.C. 112(b) have been fully considered and are found persuasive in view of the cancelled claims.
Applicants Remarks on pages 9-18 of the RCE, regarding the previous rejection of the claims under 35 U.S.C. 101 have been fully considered, but are not found persuasive or are moot in view of the amended rejection below.
On Pages 12-13 of the RCE, in disagreeing with Applicant’s assertion that the claims recite an abstract idea, Applicant argues “Claim 1 does not recite any of these types of activities recognized in the MPEP as examples of commercial interactions or of managing personal behavior or relationships between people. That is, claim 1 does not recite a transaction performance guaranty, managing a stable value protected life insurance policy via performing calculations storing pre-set limits on spending, processing insurance claims for a covered loss or policy event, filtering content, considering historical usage information while inputting data, testing a patient for nervous system malfunctions, voting, providing information to a person while avoiding interruption of their current activity, playing a dice game, assigning hair designs to balance head shape, or hedging risk…The Office Action, on page 4, acknowledges and does not dispute that the recitations in claim 1 do not match any of the examples set forth in the MPEP. Further, the Office does not identify how the recitations map onto… ‘managing personal behavior or relationships between people’ categories…Accordingly, the Applicant respectfully submits that the Office has not established a prima facie case that claim 1 or any of the other pending claims is directed to an abstract idea.”
Examiner respectfully disagrees and notes that at Step 2A, Prong One the test includes “determining whether the identified limitations(s) fall within at least one of the groupings of abstract ideas listed above”, and not necessarily one of the examples of the groupings (emphasis added). MPEP 2106.04(a)(2). Therefore, in light of the specification (e.g., Para. [0002] stating “embodiment is…for social monitoring and an analytics for proactive issue resolution” and Para. [0036] stating “allow for a social media sentiment-based incident management ticketing system that addresses the challenges of monitoring end users' social media comments regarding a particular company, brand, or other targeted subject matter…allow for the proactive monitoring of social media comments, prioritizing issues, and responding to end user concerns in a timely and effective manner”), the amended claimed method for social monitoring and analytics for proactive issue resolution in the claims recites a certain method of organizing human activity (e.g., managing personal behavior or interactions between people, including social activities); and a mental process (e.g., concepts performed in the human mind - including an observation, evaluation, judgment, opinion).
Examiner further notes MPEP 2106.07(a) explains that “When the examiner has determined the claim recites an abstract idea, the rejection should identify the abstract idea as it is recited (i.e., set forth or described) in the claim, and explain why it falls within one of the groupings of abstract ideas (i.e., mathematical concepts, mental processes, or certain methods of organizing human activity) enumerated in MPEP § 2106.04(a)(2).” In the previous final rejection dated June 2, 2026, Examiner identified the limitations that recite the abstract idea in Para. 25, and Para. 26 explained that social monitoring and analytics for proactive issue resolution fall under a certain method of organizing human activity. Therefore, it is not found persuasive that “Office has not established a prima facie case that claim 1 or any of the other pending claims [recites] an abstract idea”.
On Pages 14-15 of the RCE, Applicant further argues “The Applicant has amended claim 1 to clarify that the claimed subject matter in the present application also solves a problem that is Internet-centric….As indicated, the method involves utilizing APIs via a network to monitor, in real time, multiple platforms for posts or tags and analyzing those posts or tags from the corresponding platforms using a machine learning model and natural language processing to perform sentiment analysis, including removing words determined by the natural language processing algorithm(s) to be unnecessary (e.g., thereby improving computational efficiency) in the classification of a phrase (e.g., from a post or tag). Like claims in DDR Holdings, the recitations of amended claim 1 set forth details of how the solution to the problem is accomplished. As such, the use of the additional features, including, for example, the APIs associated with the platforms, cannot be fairly described as mere instructions to apply a judicial exception.”
Examiner respectfully disagrees that the claims are similar to DDR Holdings and notes in DDR Holdings, the court held that “the claimed solution is necessarily rooted in computer technology in order to overcome a problem specifically arising in the realm of computer networks.” Nothing in Applicant’s specification or claims describes a problem specifically arising in the realm of computer networks with a solution is necessarily rooted in computer technology in order to overcome that problem. For example, Paras. [0034] and [0043] of the specification merely discloses a network 104 at a high-level of generality (“The network 104 may be embodied as any one or more types of communication networks that are capable of facilitating communication between the various devices communicatively connected via the network 104.”), and Paras. [0035] and [0038] of the specification merely disclose the API at a high-level of generality (“the monitoring system 112 may utilize the API 118 of the social media system 106 to continuously monitoring the social media platform… different APIs 118 may be used to retrieve different types of data in some embodiment”) and nothing in the claims or specification describes a problem or a solution rooted in the “utilizing APIs via a network to monitor.. multiple platforms”. Thus, Applicant’s arguments are not found persuasive.
On Page 15 of the RCE, Applicant further argues “the claims integrate the alleged abstract idea into a practical application because they represent an improvement in a technological field…As described in paragraph [0036] of the subject application, the claims represent in an improvement in the technical field of machine-based sentiment analysis to classify sentiments in comments in Internet-based platforms and automatic transformation of the comments into dashboard tickets. Accordingly, for the foregoing reasons, the Applicant respectfully submits that the claims represent integration into a practical application.”
Examiner respectfully disagrees and notes nothing in the claims or specification recites an improvement in a technological field. Paragraph [0036] merely states “The social media sentiment-based incident management ticketing system may leverage natural language processing (NLP) and machine learning techniques to automatically detect and classify social media comments based on sentiment, topic, urgency, and/or other relevant parameters. These comments may then be transformed into incident management tickets in the respective dashboard, which may be assigned to the relevant teams for further investigation and resolution. Accordingly, these technologies allow for the proactive monitoring of social media comments, prioritizing issues, and responding to end user concerns in a timely and effective manner. The practical benefits of these technical improvements include improved end user engagement, satisfaction, and loyalty.” (emphasis added). However, nothing in the claims or specification talks about an improvement to technology of the machine-based sentiment, or natural-language processing. Rather, merely “leverag[ing]” natural language processing and machine learning techniques to perform the abstract idea, amounts to apply it or mere instructions to implement an abstract idea or other exception on a computer.
Furthermore, similar to Trading Tech, it appears Applicant is arguing a business process improvement. Classifying sentiments in comments and transforming the comments into dashboard tickets to provide “improved end user engagement, satisfaction, and loyalty” is a business process improvement rather than an improvement in the technology of sentiment analysis and natural language processing itself. See MPEP 2106.05(a)(II) “… Trading Technologies…the court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology.”
On Page 16 of the RCE, Applicant argues “each of the amended claims recites significantly more than the abstract idea, regardless of the characterization of the claims as an abstract idea.” However, Applicant fails to argue or explain why the claims recite significantly more. Therefore, Applicant’s arguments are not found persuasive.
On Page 17 of the RCE, Applicant argues “As indicated by the lack of a rejection of any of the claims under 35 U.S.C. §§ 102 or 103, the claims include features that are not well-understood, routine, or conventional. Accordingly, the Applicant further submits that at least the claimed features not taught by the art of record constitute significantly more than the abstract idea. The Applicant also hereby preemptively traverses any taking of Official Notice that one or more of the claimed features is well-understood, routine, or conventional.”
Examiner respectfully disagrees and notes that “Although the courts often evaluate considerations such as the conventionality of an additional element in the eligibility analysis, the search for an inventive concept should not be confused with a novelty or non-obviousness determination…As made clear by the courts, the “‘novelty’ of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the § 101 categories of possibly patentable subject matter.” Intellectual Ventures I v. Symantec Corp… See also Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016) (“a claim for a new abstract idea is still an abstract idea. The search for a § 101 inventive concept is thus distinct from demonstrating § 102 novelty.”). In addition, the search for an inventive concept is different from an obviousness analysis under 35 U.S.C. 103… Specifically, lack of novelty under 35 U.S.C. 102 or obviousness under 35 U.S.C. 103 of a claimed invention does not necessarily indicate that additional elements are well-understood, routine, conventional elements. Because they are separate and distinct requirements from eligibility, patentability of the claimed invention under 35 U.S.C. 102 and 103 with respect to the prior art is neither required for, nor a guarantee of, patent eligibility under 35 U.S.C. 101. The distinction between eligibility (under 35 U.S.C. 101) and patentability over the art (under 35 U.S.C. 102 and/or 103) is further discussed in MPEP § 2106.05(d).) See MPEP 2106.05 Eligibility Step 2B: Whether a Claim Amounts to Significantly More (emphasis added). Thus, Applicant’s arguments are not found persuasive.
On Pages 19-20 of the RCE, in discussing Ex Parte Desjardins, Applicant states “Similar to the claims of the subject application, the claims at issue in Ex Parte Desjardins were directed to a complect algorithm that involved machine learning” and “respectfully requests that such directive [to not evaluate claims at such a high level of generality] be followed.”
Examiner respectfully disagrees that Applicant’s claims are similar to those of Ex Parte Desjardins, and notes that the mere recitation of performing and generating functions “with a machine learning model” is not similar to the specification identified improvements as to how the machine learning model itself operates of Ex Parte Desjardins. Specifically, the specification in Desjardins identified the improvement to machine learning technology by explaining how the machine learning model is trained to learn new tasks while protecting knowledge about previous tasks to overcome the problem of “catastrophic forgetting,” and that the claims reflected the improvement identified in the specification. Nothing in Applicant’s claims or specification describes a similar improvement. Thus, Applicant’s arguments are not found persuasive.
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, 5-8, 10-11, 15-18, 20 and 22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1, 5-8, 10 and 22 are directed to a method (i.e., a process), and claims 11, 15-18, and 20 are directed to a system comprising at least one processor (i.e., a machine), and therefore the claims all fall within one of the four statutory categories of invention.
Step 2A, Prong One
Claims 1 and 11 recites a series of steps/functions of: social monitoring and analytics for proactive issue resolution, comprising: monitoring each of multiple social media platforms for a plurality of an end user's references to a plurality of relevant keywords in one or more posts or tags using a search operation, wherein the plurality of relevant keywords is indicative as to a sentiment associated with each end users’ reference in the one or more posts or tags; performing a sentiment analysis on a current end user's reference to the plurality of keywords to determine a current sentiment of the current end user's reference based on a classification of negative sentiment and non-negative sentiment, wherein the classification of negative sentiment and non-negative sentiment is determined with the sentiment analysis on the plurality of relevant keywords included in each end user's reference provided to the corresponding social media platform; analyzing, with algorithms, each negative phrase included in the current end user's reference that is classified as negative sentiment based on the classification of negative sentiment and non-negative sentiment to remove unnecessary words from the negative phrase of the current end user's reference, wherein the unnecessary words are not required to classify the negative phrase of the current end user's reference as being the negative phrase; generating a current negative phrase associated with the current end user's reference to the plurality of keywords in response to determining that the sentiment of the current end user's reference is a negative phrase based on identifying that the current end user’s references of the current negative phrase with unnecessary words removed is the negative phrased based on the classification of negative and non-negative sentiment; determining a set of existing dashboard tickets that are possible matches to the current negative phrase of the current end user’s reference in response to generating the current negative phrase associated with the current end user's reference to the plurality of keywords within the unnecessary words removed; comparing the current negative phrase to each existing dashboard ticket of the set of existing dashboard tickets that are the possible matches to identify a closest matching existing dashboard ticket, including determining whether a similarity between the current negative phrase and the closest matching existing dashboard ticket exceeds a threshold; increasing a priority of the closest matching existing dashboard ticket in response to determining that the similarity between the negative phrase and the closest matching existing dashboard ticket exceeds the threshold by incrementing a counter indicative of a frequency associated with the issue; and updating with feedback as to a final status of the closest matching existing dashboard ticket associated with the current negative phrase for additional end user’s references that are determined as similar to the current negative phrase.
The claims as a whole recite a certain method of organizing human activity, and a mental process. The limitations recited above of social monitoring and analytics for proactive issue resolution, (under broadest reasonable interpretation) recite the abstract idea of a certain method of organizing human activity, e.g., managing personal behavior or relationships or interactions between people (including social activities); and a mental process, e.g., concepts performed in the human mind (including an observation, evaluation, judgment). The mere recitation of generic computer components recited at a high-level of generality, does not take the claim out of the certain methods of organizing human activity grouping and mental process. Thus, the claims recite an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. Claims 1 and 11 as a whole amount to: “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea; and do no more than generally link the use of a judicial exception to a particular technological environment or field of use (machine learning, and natural language processing), as discussed in MPEP § 2106.05(h).
The additional element of: (i) a computing system in claim 1, is recited at a high-level of generality such that, when viewed as whole/ordered combination, it amounts to “apply it” (or an equivalent) with the judicial exception, or merely includes 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)).
The additional element of: (ii) real-time monitoring in claims 1 and 11, is recited at a high-level of generality such that, when viewed as whole/ordered combination, it amounts to “apply it” (or an equivalent) with the judicial exception, or merely includes 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)).
The additional element of: (iii) a network in claims 1 and 11, is recited at a high-level of generality such that, when viewed as whole/ordered combination, it amounts to “apply it” (or an equivalent) with the judicial exception, or merely includes 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)).
The additional element of: (iv) application programming interface in claims 1 and 11, are recited at a high-level of generality such that, when viewed as whole/ordered combination, it amounts to “apply it” (or an equivalent) with the judicial exception, or merely includes 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)).
The additional elements of: (v) at least one processor; and at least one memory comprising a plurality of instructions stored thereon in claim 11, are recited at a high-level of generality such that, when viewed as whole/ordered combination, it amounts to “apply it” (or an equivalent) with the judicial exception, or merely includes 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)).
The additional element of: (vi) a machine learning model (performing functions, analyzing, generating and being updated) in claims 1 and 11, are recited at a high-level of generality such that, when viewed as whole/ordered combination, it does no more than generally link the use of a judicial exception to a particular technological environment or field of use (machine learning), as discussed in MPEP § 2106.05(h).
The additional element of: (vii) a natural language processing algorithm (analyzing and identifying) in claims 1 and 11, are recited at a high-level of generality such that, when viewed as whole/ordered combination, it does no more than generally link the use of a judicial exception to a particular technological environment or field of use (natural language processing), as discussed in MPEP § 2106.05(h).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination (See Fig. 1), do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, the claim is directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional elements amount to no more than reciting the words “apply it” (or an equivalent) with the judicial exception, or merely include instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea; and generally linking the use of a judicial exception to a particular technological environment or field of use (machine learning, and natural language processing).
The same analysis applies here in 2B, i.e., reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea (See MPEP 2106.05(f)), and generally linking the use of a judicial exception to a particular technological environment or field of use (machine learning; and natural language processing) (See MPEP § 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional elements do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, the claims are ineligible.
Claims 5-8, 10, 15-18, 20 recite details in the claim limitations which merely narrow the previously recited abstract idea limitiaitions. For these reasons, described above with respect to claims 1 and 11, these judicial exceptions, when viewed as a whole/ordered combination, are not meaningfully integrated into a practical application or significantly more than the abstract idea. Thus, claims 5-10 and 15-21 are ineligible.
Claim 22 recites the additional element of wherein the machine learning model is a neural network, which is recited at a high-level of generality such that, when viewed as whole/ordered combination, do no more than generally link the use of a judicial exception to a particular technological environment or field of use (machine learning/neural networks), See MPEP § 2106.05(h). Therefore, the abstract idea is not integrated into a practical application.
The claim does not include limitations sufficient, either alone or in combination, to amount to significantly more than the claimed abstract idea because the aforementioned additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (machine learning/neural network) See MPEP § 2106.05(h)
Prior Art
The claims are allowable over the prior art. The prior art fails to reasonably teach or suggest, the combination of all limitations in the independent claims. The closest prior art includes:
U.S. Patent Application Publication No. 2016/0043913 to Mukherjee et al. (hereinafter “Mukherjee”). Mukherjee discloses monitoring one or more social media accounts by crawling social media and analyzing keywords within this thread.
“On Stopwords, Filtering and Data Sparsity for Sentiment Analysis of Twitter” by Saif et al., dated January, 2014 (hereinafter “Saif”). Saif discloses stopwords as meaningless words that have low discrimination power. The earliest work on stopwords removal suggests that words in natural language texts can be divided into keyword terms and non-keyword terms.
U.S. Patent Application Publication No. 2024/0095759 to Murata et al. (hereinafter “Murata”). Murata discloses a method for processing information from a social platform and triggering an action such as creating a ticket is provided. The method includes monitoring information on a social platform, based on predetermined keywords set by a system user, extracting information related to a service from the social platform, the extracted information containing of the predetermined keywords, and determining a sentiment value associated with the extracted information, assigning the extracted information to a sentiment category based on the sentiment value.
U.S. Patent No. 10,270,644 to Valsecchi et al. (hereinafter “Valsecchi”). Valsecchi discloses a MLA engine that uses the feedback to update the machine learning model. For example, feedback received from the user may indicate that a trouble ticket should not have been, and the MLA engine may incorporate the feedback into the machine learning model (e.g., by training the machine learning model) so a score assigned to the same or similar alarm in the future will be reduced.
U.S. Patent Application Publication No. 2008/0267312 to Yokoyama (hereinafter “Yokoyama”). Yokoyama discloses that the data stream halting processing is repeated in increasing order of the priority of user until the peak evaluation result becomes OK (not larger than the threshold).
U.S. Patent Application Publication No. 2020/0258013 to Monnett et al. (hereinafter “Monnett”). Monnett discloses a machine learning model that receives communication associated with support ticket, and determines content data, metadata, and context data for communication; and uses first channel value and second channel value to generate priority associated with support ticket, and outputs priority.
U.S. Patent Application No. 2021/0209307 to Serna (hereinafter “Serna”). Serna discloses sentiment analysis may be based on aggregating communications between a first individual, group or entity and a second individual, group or entity. Sentiment analysis may include mining social media to recover a plurality of artifacts.
Relevant Prior Art
The following art, not cited, is considered relevant:
“To Use or Lose: Stop Words in NLP” by Moirangthem Singh, dated August 29, 2023 (hereinafter “Singh”). Singh discloses that stopwords can be categorized into generic stop words, and domain-specific stopwords.
U.S. Patent No. 9,747,275 to Barness et al. (hereinafter “Barness”). Barness discloses if an NLP comparison of the composed-message writing style and the composer's writing habits identifies that the composed message is far longer and repetitious than normal, semantic and syntactic analysis may be performed on the composed message content to identify for removal repeated statements or ideas.
Conclusion
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/RUPANGINI SINGH/
Primary Examiner, Art Unit 3628
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