DETAILED ACTION
This action is in response to the amendment filed on 12/11/2025, which has been entered into the above identified application. Claims 1-3, 6-10, 13-17, and 20 are pending in the application and have been examined.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16th, 2013 is being examined under the first inventor to file provisions of the AIA .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 12/11/2025 has been entered.
The status of the claims is as follows.
Claims 1, 7, 8, 14, 15 and 20 are amended and Claims 4-5, 11-12 and 18-19 are cancelled. Claims 1-3, 6-10, 13-17, and 20 are currently pending.
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 1-3, 6-10, 13-17, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1,
(Step 1): Claim 1 recites a system comprising at least one hardware processor, thus a machine, one of the four statutory categories of patentable subject matter.
(Step 2A Prong 1): However, Claim 1 further recites to train a next response prediction (NRP) machine learning model on a training dataset comprising a plurality of entries which falls in the mathematical concept grouping of abstract ideas;
inference … to output a level of significance of each utterance in the dialog with respect to performing an NRP task over the dialog, which falls in the mental process grouping of abstract ideas;
predicting … a next utterance at a specified point in the dialog which falls in the mental process grouping of abstract ideas;
its level of significance is determined by … calculating a difference between a probability … associated with the predicting when the utterance is included in the dialog context and a probability … associated with the predicting when the utterance is removed from the dialog context which falls in the mental process grouping of abstract ideas;
assign a score to each of the utterances in the dialog, based, at least in part, on the determined level of significance, which falls in the mental process grouping of abstract ideas;
and select one or more of the utterances for inclusion in an extractive summarization of the dialog, based, at least in part, on the assigned scores, which falls in the mental process grouping of abstract ideas. Thus, Claim 1 recites an abstract idea.
(Step 2A Prong 2): The claim does not recite any additional elements which integrate the abstract idea into a practical application, because the additional elements consist of:
a) at least one hardware processor and a non-transitory computer-readable storage having stored thereon program instructions, the program instructions executable by the at least one hardware processor to:, which is implementing an abstract idea on generic computer components (MPEP 2106.05(f))
b) receive, as input, a two-party multi-turn dialog which is insignificant extra-solution activity of data collection (MPEP 2106.05(g))
c) by the trained NRP machine learning model inferencing over the dialog which is implementing an abstract idea on generic computer components (MPEP 2106.05(f))
d) via the NRP machine learning model from a provided set of candidate utterances, which is implementing an abstract idea on generic computer components (MPEP 2106.05(f))
e) based on an input dialog context comprising a sequence of utterances appearing in the dialog before the specified point, which merely recites the particular technological environment or field of use in which the abstract idea is to be performed (MPEP 2106.05(h))
f) the NRP machine learning model calculating, which is implementing an abstract idea on generic computer components (MPEP 2106.05(f))
g) output by the NRP machine learning model, which is implementing an abstract idea on generic computer components (MPEP 2106.05(f))
and thus, the claim is directed to the abstract idea of determining and arbitrarily scoring the significance of utterances in a dialog, as well as selecting utterances for inclusion in an extractive summary depending on their score.
(Step 2B): The additional elements, taken alone or in combination, cannot provide significantly more than the abstract idea itself, because element a), c), d), f) and g) (via MPEP 2106.05(f), “apply it on a computer”) cannot provide an inventive concept, element b) is well-understood, routine, and conventional (by MPEP 2106.05(d), “transmitting or receiving data over a network”), and element e) (via MPEP 2106.05(h)) cannot integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself. Thus, Claim 1 is subject-matter ineligible.
Claims 2 and 7, dependent upon Claim 1, merely recite the particular technological environment or field of use in which the abstract idea is to be performed, i.e., customer service field of use and data used in the mental processes, which by MPEP 2106.05(h) cannot integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself.
Claims 3 and 6, dependent upon Claim 1, merely recite additional steps of the abstract idea (Claim 3: predicting previous utterances at a specified point in the dialog; Claim 6: selecting utterances with score exceeding a threshold) but no new additional elements (MPEP 2106.05(f); Claim 6 only repeats the selecting/”apply it on a computer” limitation of Claim 1) and thus no new additional elements which, alone or in combination, could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself.
Claims 8-10, 13-14 recite the method performed by the system of Claims 1-3, 6 and 7, and are thus rejected for reasons set forth in the rejection of Claims 1-3, 6 and 7, respectively. Similarly, Claims 15-17, 20 recite a computer program product comprising the non-transitory computer readable medium of Claims 1-3, and 7 respectively, and are thus rejected for reasons set forth in the rejection of Claims 1-3 and 7, respectively.
Response to Arguments
The Examiner acknowledges the Applicant’s amendments to Claims 1, 8, 15 and 20.
Applicant’s arguments filed December 11th, 2025, traversing the rejection of claims 1-3, 6-10, 13-17, and 20 under 35 U.S.C. § 101 have been fully considered, but are not fully persuasive.
Applicant alleges, on page 9 of the Remarks, that the claimed advance of independent claims 1, 8, and 15, as amended, are not an abstract idea under the mental process grouping. More specifically, the claimed invention is not a mental process since the claimed invention involves, at least, inferencing by a machine learning model over an input dialog to predict a next utterance based on the input dialog context and to output a level of utterance significance by calculating a difference between a probability associated with a prediction when the utterance is included in the dialog context and a probability associated with a prediction when the utterance is excluded from the dialog context, where the probabilities are also output by the machine learning model. Applicant's arguments which expressly refer to independent claims 1, 8, and 15 are equally applicable to all dependent claims by virtue of their dependencies on the independent claims.
Examiner respectfully disagrees. Examiner maintains that “inferencing … over an input dialog to predict a next utterance based on the input dialog context” is a mental process step. One is able to read over inputted dialog and, at each utterance of the input dialog context, predict a next potential utterance in the input dialog. Such analysis of the input dialog context and subsequent prediction of next utterances given the input dialog context reads as a mental process abstract idea step. Its performance by a machine learning model constitutes the additional element of implementing aforementioned abstract idea on generic computing components (via MPEP 2106.05(f), “apply it on a computer”). As a result, inferencing by a machine learning model over a given input dialog to output a level of significance is simply the mental process abstract idea of determining an outputted level of significance by analyzing utterances in the dialog with respect to performing the NRP task.
Examiner maintains that calculating a difference between a probability associated with a prediction when the utterance is included in the dialog context and a probability associated with a prediction when the utterance is excluded from the dialog context is a mental process abstract idea step since one of ordinary skill in the art could determine how likely or easy it is to guess the next utterance in a dialog when certain utterances are present or missing from the dialog context. As such, calculating a difference would simply be the mental process of determining such probabilities associated with the utterance being present versus the utterance being missing before subsequently determining the difference between the two. The probabilities being specified to be “output by the NRP machine learning model” again reads on performance of the abstract idea (and its abstract idea step) by a machine learning model over given input dialogs, thus constituting the additional element of implementing aforementioned abstract idea step on generic computing components (via MPEP 2106.05(f), “apply it on a computer”). No present additional elements incorporate the abstract idea into practical application nor recite technological improvements, and thus the claim remains directed to the abstract idea.
The rejection of Claim 1 under 35 U.S.C. § 101 has been maintained. Similarly, the rejection of Claims 8 and 15 under 35 U.S.C. § 101 have been maintained.
The rejection of Claims 2-3 and 6-7 under 35 U.S.C. § 101, which depend directly or indirectly from Claim 1, have been maintained. The rejection of Claims 9-10 and 13-14, which depend directly or indirectly from Claim 8, have been maintained. Rejection of Claims 16-17 and 20, under 35 U.S.C. § 101, which depend directly or indirectly from Claim 15, have been maintained.
Conclusion
Applicant’s amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 JONATHAN J KIM whose telephone number is (571)272-0523. The examiner can normally be reached 8-6.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matt El can be reached on (571) 270-3264. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JONATHAN J KIM/Examiner, Art Unit 2141
/MATTHEW ELL/Supervisory Patent Examiner, Art Unit 2141