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 . 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 (i.e., changing from AIA to pre-AIA ) 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.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. The applicant's submission, the “AMENDMENT WITH RCE” filed on 06 February 2026 (hereinafter referred to as the “Amendment”) has been entered.
Status of the Claims
The pending claims in the present application are claims 1-8 and 10-21 of the Amendment.
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 1-8 and 10-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The paragraphs below provide rationales for the rejection. The rationales are based on the multi-step subject matter eligibility test outlined in MPEP 2106.
Step 1 of the eligibility analysis involves determining whether a claim falls within one of the four enumerated categories of patentable subject matter recited in 35 USC 101. (See MPEP 2106.03(I).) That is, Step 1 asks whether a claim is to a process, machine, manufacture, or composition of matter. (See MPEP 2106.03(II).) Referring to the pending claims, the “method” of claims 1-8, 10, 11, and 21 constitutes a process under 35 USC 101, the “apparatus” of claims 12-19 constitutes a machine under the statute, and the “computer program product” of claim 20 constitutes a manufacture under the statute. Accordingly, claims 1-8 and 10-21 meet the criteria of Step 1 of the eligibility analysis. The claims, however, fail to meet the criteria of subsequent steps of the eligibility analysis, as explained in the paragraphs below.
The next step of the eligibility analysis, Step 2A, involves determining whether a claim is directed to a judicial exception. (See MPEP 2106.04(II).) This step asks whether a claim is directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea. (See id.) Step 2A is a two-prong inquiry. (See MPEP 2106.04(II)(A).) Prong One and Prong Two are addressed below.
In the context of Step 2A of the eligibility analysis, Prong One asks whether a claim recites an abstract idea, law of nature, or natural phenomenon. (See MPEP 2106.04(II)(A)(1).) Using claim 1 as an example, the claim recites the following abstract idea limitations:
“A method for generating an insight report, the method comprising: ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., creating a document showing information)
“... receiving ... a configured input data set, wherein the configured input data set comprises (i) a source document set and (ii) a configuration parameter set; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., receiving documents and instructions for analyzing the documents)
“... selecting ... configuration based on the configuration parameter set; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., planning how to analyze the documents based on instructions)
“... generating, ... based on the configuration parameter set, (a) an interest population document subset for an interest population and (b) a reference population document subset for a reference population, wherein the interest population document subset includes documents from the source document set that satisfy interest population criteria and the reference population document subset includes documents of the source document set that satisfy reference population criteria, wherein the interest population criteria comprises a particular time frame of interest; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., generating, based on instructions, a list of documents that might be of interest to a party, and a list of documents that meet various criteria, including timeframe criteria)
“... generating, ... based on the interest population document subset, an n-gram term set; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., thinking about a phrase from, or otherwise based on, text in documents)
“... determining ... at least one of (a) an n-gram ratio lift value for each n-gram term in the n-gram term set and (b) a weighted n-gram ratio lift value for each n-gram term in the n-gram term set, wherein the n-gram ratio lift value and the weighted n-gram ratio lift value for an n-gram term are determined based on a frequency of the n-gram term within the interest population document subset and the reference population document subset; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., scoring the phrases based on how frequently they appear in documents)
“... generating, ... based on an associated n-gram ratio lift value or associated weighted n-gram ratio lift value for an n-gram term in the n-gram term set, an n-gram term payload comprising one or more n-gram terms; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., focusing in on certain phrases)
“... applying, .. based on a configuration parameter from the configuration parameter set, a filter to the n-gram term payload; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., filtering phrases to differentiate between the phrases)
“... generating, ... based on the n-gram term payload, an interest population relevant document subset, wherein the interest population relevant document subset comprises one or more documents from the interest population document subset that include an n-gram term included in the n-gram term payload; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., identifying documents that have specific phrases)
“... generating ... an emerging topic set for an interest population, wherein the emerging topic set comprises one or more topic identifiers and each topic identifier is associated with an n-gram term in the n-gram term payload; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., identifying topics that may be of interest to a party based on the text and phrase analyses above)
“... generating, ... based on the interest population relevant document subset, an interest population topic document subset for each topic identifier included in the emerging topic set, wherein the interest population topic document subset comprises one or more documents of the interest population relevant document subset which include an n-gram term associated with a corresponding topic identifier; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., identifying documents that relate to the topics based on the documents having the phrases related to the topics of interest)
“... generating ... a context snippet for each topic identifier included in the emerging topic set using a corresponding interest population topic document subset; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., providing a summaries relating to the topics using the documents identified as being related to the topics)
“... generating, simultaneously ..., a per-topic metric set for each topic identifier included in the emerging topic set, wherein the per-topic metric set comprises one or more per-topic metrics related to the one or more n-gram terms associated with a corresponding topic identifier; ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., calculating metrics for identified topics that may include frequency or other metrics of various phrases related to the topics)
“... generating ... the insight report, wherein the insight report comprises each per-topic metric set for each topic identifier included in the emerging topic set and each context snippet for each topic identifier included in the emerging topic set; and ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., writing up a report with the metrics, summaries, and the like, for identified topics)
“... providing ... the insight report ...” - See below regarding MPEP 2106.04(a), mental processes (e.g., giving or otherwise communicating the report to a party)
The above-listed limitations of claim 1, when applying their broadest reasonable interpretations in light of their context in the claim as a whole, fall under enumerated groupings of abstract ideas outlined in MPEP 2106.04(a). For example, limitations of the claim can be characterized as concepts performed in the human mind, including observation (e.g., the recited “receiving” and “providing” steps), and evaluation, judgment, and/or opinion (e.g., the recited “selecting,” “generating,” “determining,” and “applying” steps), which fall under the mental processes grouping of abstract ideas (see MPEP 2106.04(a)). Accordingly, for at least these reasons, claim 1 fails to meet the criteria of Step 2A, Prong One of the eligibility analysis.
In the context of Step 2A of the eligibility analysis, Prong Two asks if the claim recites additional elements that integrate the judicial exception into a practical application. (See MPEP 2106.04(II)(A)(2).) Continuing to use claim 1 as an example, the claim recites the following additional element limitations:
The claimed “receiving” is performed “by communications hardware” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The claimed “selecting” is performed “by an insight engine” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The claimed “configuration” is for the “insight engine” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The claimed “generating,” “determining,” and “applying” are performed “by the insight engine” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The claimed “providing” is performed “by the communications hardware and in real-time” and “to a facility device” - See below regarding MPEP 2106.05(a)-(c) and (f)-(h)
The above-listed additional element limitations of claim 1, when applying their broadest reasonable interpretations in light of their context in the claim as a whole, are analogous to: accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, mere automation of manual processes, which courts have indicated may not be sufficient to show an improvement in computer-functionality (see MPEP 2106.05(a)(I)); a commonplace business method being applied on a general purpose computer, and selecting a particular generic function for computer hardware to perform (e.g., buffering content) from within a range of fundamental or commonplace functions performed by the hardware, which courts have indicated may not be sufficient to show an improvement to technology (see MPEP 2106.05(a)(II)); a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions, and merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions, which do not qualify as a particular machine or use thereof (see MPEP 2106.05(b)(I)); a machine that is merely an object on which the method operates, which does not integrate the exception into a practical application (see MPEP 2106.05(b)(II)); use of a machine that contributes only nominally or insignificantly to the execution of the claimed method, which does not integrate a judicial exception (see MPEP 2106.05(b)(III)); transformation of an intangible concept such as a contractual obligation or mental judgment, which is not likely to provide significantly more (see MPEP 2106.05(c)); use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea, a commonplace business method or mathematical algorithm being applied on a general purpose computer, and requiring the use of software to tailor information and provide it to the user on a generic computer, which courts have found to be mere instructions to apply an exception, because they do no more than merely invoke computers or machinery as a tool to perform an existing process (see MPEP 2106.05(f)); mere data gathering in the form of obtaining information about transactions using the Internet to verify the transactions and consulting and updating an activity log, which courts have found to be insignificant extra-solution activity (see MPEP 2106.05(g)); and specifying that the abstract idea of monitoring audit log data relates to transactions or activities that are executed in a computer environment, because this requirement merely limits the claims to the computer field, i.e., to execution on a generic computer, which courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception (see MPEP 2106.05(h)). For at least these reasons, claim 1 fails to meet the criteria of Step 2A, Prong Two of the eligibility analysis.
The next step of the eligibility analysis, Step 2B, asks whether a claim recites additional elements that amount to significantly more than the judicial exception. (See MPEP 2106.05(II).) The step involves identifying whether there are any additional elements in the claim beyond the judicial exceptions, and evaluating those additional elements individually and in combination to determine whether they contribute an inventive concept. (See id.) The ineligibility rationales applied at Step 2A, Prong Two, also apply to Step 2B. (See id.) For all of the reasons covered in the analysis performed at Step 2A, Prong Two, claim 1 fails to meet the criteria of Step 2B. Further, claim 1 also fails to meet the criteria of Step 2B because at least some of the additional elements are analogous to: receiving or transmitting data over a network, e.g., using the Internet to gather data, which courts have recognized as well-understood, routine, conventional activity, and as insignificant extra-solution activity (see MPEP 2106.05(d)(II)(i), which states, “Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added))”). As a result, claim 1 is rejected under 35 USC 101 as ineligible for patenting.
Regarding claims 2-8, 10, 11, and 21, the claims depend from claim 1, and expand upon limitations introduced by claim 1. The claims are rejected at least for the same reasons as claim 1. For example, the claims recite abstract idea elements similar to the abstract idea elements of claim 1, that fall under the same abstract idea groupings as the abstract idea elements of claim 1 (e.g., the “for each n-gram term included in the n-gram term set: determining ... an interest population n-gram term ratio for the interest population, and determining ... a reference population n-gram term ratio for the reference population, wherein a corresponding n-gram ratio lift for the n-gram term is determined based on the interest population n-gram term ratio and the reference population n-gram term ratio, wherein a corresponding weighted n-gram ratio lift value for the n-gram term is determined based on the corresponding n-gram ratio lift and a frequency the n-gram term appears within the interest population document subset; ranking ... each n-gram term included in the n-gram term set based on at least one of a corresponding n-gram ratio lift or a corresponding weighted n-gram ratio lift associated with each n-gram term; and generating ... a topic identifier for each n-gram term of the n-gram term payload” of claim 2, the “generating, ... based on the n-gram term payload, a reference population relevant document subset, wherein the reference population relevant document subset comprises one or more documents of the reference population document subset which include an n-gram term of the n-gram term payload” of claim 3, the “generating ... an n-gram pair set, wherein (i) the n-gram pair set comprises one or more n-gram pairs and (ii) each n-gram pair includes a first n-gram term and a second n-gram term from the n-gram term payload; for each n-gram pair included in the n-gram pair set: determining, ... based on the interest population relevant document subset, an interest population n-gram pair score, determining, ... based on the reference population relevant document subset, a reference population n-gram pair score, determining, ... based on the interest population relevant document subset, an interest population pair confidence, determining, ... based on the reference population relevant document subset, a reference population pair confidence, determining, ... based on the interest population n-gram pair score and the reference population n-gram pair score, a n-gram an n-gram pair lift, and determining, ... based on the interest population pair confidence and the reference population pair confidence, a n-gram pair confidence lift; ranking ... each n-gram pair included in the n-gram pair set based on at least one of an associated interest population n-gram pair score, an associated n-gram pair lift, or an associated n-gram pair confidence lift; generating, ... based on an associated n-gram pair ranking, an n-gram pair payload comprising one or more n-gram pairs; applying, ... based on one or more configuration parameters from the configuration parameter set, a filter to the n-gram pair payload; and generating ... a topic identifier for each n-gram pair of the n-gram pair payload” of claim 4, the “generating ... an n-gram pair combination set, wherein (i) the n-gram pair combination set comprises one or more n-gram pair combinations and (ii) each n-gram pair combination includes a first n-gram pair and a second n-gram pair from the n-gram pair payload; generating ... a first n-gram pair document subset, wherein the first n-gram pair document subset comprises one or more documents from at least the interest population document subset or the reference population document subset which include the first n-gram pair of the one or more n-gram pair combinations; generating ... a second n-gram pair document subset, wherein the second n-gram pair document subset comprises one or more documents from at least the interest population document subset or the reference population document subset which include the second n-gram pair of the one or more n-gram pair combinations; generating ... an overlap n-gram pair document subset, wherein the overlap n-gram pair document set comprises one or more documents which are included in both the first n-gram pair document subset and the second n-gram pair document subset; generating ... an interest population overlap n-gram pair combination document subset, wherein the interest population overlap n-gram pair combination document subset includes documents of the overlap n-gram pair document subset which satisfy interest population criteria; and generating ... a reference population overlap n-gram pair combination document subset, wherein the reference population overlap n-gram pair combination document subset includes documents of the overlap n-gram pair document subset which satisfy reference population criteria” of claim 5, the “for each n-gram pair combination included in the n-gram pair payload: determining ... an interest population n-gram pair combination ratio for the interest population, determining ... a reference population n-gram pair combination ratio for the reference population, determining, ...based on the interest population n-gram pair combination ratio and the reference population n-gram pair combination ratio, an n-gram pair combination lift for the one or more n-gram pair combinations, and determining, ... based on the n-gram pair combination lift, whether an n-gram pair combination threshold is satisfied” of claim 6, the “in response to determining the n-gram pair combination threshold is satisfied: determining ... an interest population n-gram pair combination score, determining ... an interest population n-gram pair combination confidence, determining, ... based on at least one of the interest population n-gram pair combination score or the interest population n-gram pair combination confidence, whether a topic threshold is satisfied, and in response to determining a topic threshold is satisfied, generating a topic identifier for the one or more n-gram pair combinations” of claim 7, the “for each topic identifier included in the emerging topic set: generating ... a reference population topic document subset from the source document set for the reference population, wherein the reference population topic document subset includes documents of a reference population document subset which include one or more n-gram terms associated with a corresponding topic identifier topic identifier; determining ... an interest population topic ratio for the interest population, determining ... a reference population topic ratio for the reference population, and determining, ... based on the interest population topic ratio and the reference population topic ratio, a topic ratio lift for the one or more topic identifiers, wherein each topic identifier included in the emerging topic set is ordered based on an associated topic ratio lift” of claim 8, the “for each topic identifier included in the emerging topic set: generating ... an interest population topic document subset from the source document set for the interest population, wherein the interest population topic document subset includes documents of an interest population document subset which include one or more n-gram terms associated with a corresponding topic identifier, and selecting ... one or more documents from the interest population topic document subset in which an n-gram term associated with the topic identifier appears most frequently” of claim 10, the “assigning ... a group identifier to two or more topic identifiers included in the emerging topic set, wherein the group identifier is assigned to topic identifiers which include one or more of same associated n-gram terms” of claim 11, and the “wherein (a) the configuration parameter set comprises a filter and (b) the filter defines at least one of (i) a minimum proportion of documents an n-gram term must occur within, (ii) a maximum number of documents an n-gram term can occur within for a reference population, (iii) a minimum number of documents which associated n-gram terms occur in, (iv) a maximum number of n-gram terms that may be included in an n-gram payload, (v) a maximum number of occurrences of an n-gram term within a portion of documents, (vi) a minimum ratio lift for an n-gram term, (vii) a minimum number of documents for an n-gram pair, (viii) a minimum proportion of documents a second n-gram term of an n-gram pair must occur in, (ix) a maximum number of topic identifiers for an emerging topic set, (x) a minimum proportion of documents associated n-gram terms of a topic identifier must occur within, (xi) a minimum topic ratio lift for a n-gram term combination, (xii) a minimum percent increase within an interest population group for a n-gram term combination, (xiii) a maximum number of topic identifiers ordered based on document size, (xix) a maximum number of topic identifiers based on topic ratio lift and (xx) a maximum number of topic identifiers for an emerging topic set” of claim 21). The dependent claims recite further additional elements that are similar to the additional elements of claim 1, that fail to warrant eligibility for the same reasons as the additional elements of claim 1 (e.g., the “by the insight engine” of claims 2-8, 10, and 11). Accordingly, claims 2-8, 10, 11, and 21 also are rejected as ineligible under 35 USC 101.
Regarding claims 12-19, while the claims are of different scope relative to claims 1-8, the claims recite limitations similar to the limitations of claims 1-8. As such, the rejection rationales applied to reject claims 1-8 also apply for purposes of rejecting claims 12-19. Limitations recited by claims 12-19 that do not have a counterpart in claims 1-8, such as the recited “apparatus” limitation of claim 12, fails to warrant a finding of eligibility, because the limitation amounts to an additional element that fails to meet the criteria of Step 2A, Prong Two and Step 2B, for the same reasons as the additional elements of claims 1-8. Claims 12-19 are, therefore, also rejected as ineligible under 35 USC 101.
Regarding claim 20, while the claim is of different scope relative to claim 1 and to claim 12, the claim recites limitations similar to the limitations of claims 1 and 12. As such, the rejection rationales applied to reject claims 1 and 12 also apply for purposes of rejecting claim 20. Limitations recited by claim 20 that do not have a counterpart in claims 1 and 12, such as the recited “computer program product for generating an insight report, the computer program product comprising at least one non-transitory computer-readable storage medium storing software instructions that, when executed, cause an apparatus to” limitation of claim 20, fails to warrant a finding of eligibility, because the limitation amounts to an additional element that fails to meet the criteria of Step 2A, Prong Two and Step 2B, for the same reasons as the additional elements of claims 1 and 12. Claim 20 is, therefore, also rejected as ineligible under 35 USC 101.
Examiner Remarks
This Office Action does not assert any prior art rejections against pending claims 1-8 and 10-21. In the previous Office Action, claims were rejected under 35 USC 103 as obvious in view of combinations of the cited Herath (U.S. Pat. App. Pub. No. 2024/0112197 A1), Balduino (U.S. Pat. App. Pub. No. 2019/0362021 A1), and Tiwari (U.S. Pat. App. Pub. No. 2019/0102374 A1) references. The obviousness rejections have been withdrawn, because the claims distinguish over the cited references. For example, Herath discloses, “Arrangements for providing emerging topic detection” (Abstract), consideration of “text data” including “a first body of terms for a first time period and a second body of terms for a second time period” (Abstract), wherein “emerging terms and/or associated categories may be transmitted to a computing device for display on a dashboard” (Abstract), and “generating the body of terms for different time periods may include generating a document term matrix representing terms (e.g., which terms, number of appearances, and the like) appearing in each document (e.g., each text description of associate and customer interactions) for each time period” (para. [0031]). These features of Herath read on recited limitations. Herath does not, however, disclose or suggest differentiating between subsets of documents, and performing steps based thereon. For example, generating document term matrices, in Herath, does not appear to involve generating different document subsets, and further generating additional subsets based thereon. As such, Herath fails to disclose or suggest the recited “generating, by the insight engine and based on the configuration parameter set, (a) an interest population document subset for an interest population and (b) a reference population document subset for a reference population, wherein the interest population document subset includes documents from the source document set that satisfy interest population criteria and the reference population document subset includes documents of the source document set that satisfy reference population criteria, wherein the interest population criteria comprises a particular time frame of interest; generating, by the insight engine and based on the interest population document subset, an n-gram term set; determining, by the insight engine, at least one of (a) an n-gram ratio lift value for each n-gram term in the n-gram term set and (b) a weighted n-gram ratio lift value for each n-gram term in the n-gram term set, wherein the n-gram ratio lift value and the weighted n-gram ratio lift value for an n-gram term are determined based on a frequency of the n-gram term within the interest population document subset and the reference population document subset; generating, by the insight engine and based on an associated n-gram ratio lift value or associated weighted n-gram ratio lift value for an n-gram term in the n-gram term set, an n-gram term payload comprising one or more n-gram terms; applying, by the insight engine and based on a configuration parameter from the configuration parameter set, a filter to the n-gram term payload; generating, by the insight engine and based on the n-gram term payload, an interest population relevant document subset, wherein the interest population relevant document subset comprises one or more documents from the interest population document subset that include an n-gram term included in the n-gram term payload; generating, by the insight engine, an emerging topic set for an interest population, wherein the emerging topic set comprises one or more topic identifiers and each topic identifier is associated with an n-gram term in the n-gram term payload; generating, by the insight engine and based on the interest population relevant document subset, an interest population topic document subset for each topic identifier included in the emerging topic set, wherein the interest population topic document subset comprises one or more documents of the interest population relevant document subset which include an n-gram term associated with a corresponding topic identifier” limitations of claim 1. Neither Balduino nor Tiwari remedies the deficiencies of Herath. Claim 1 is, therefore, allowable over Herath, Balduino, and Tiwari. Claims 12 and 20 recite limitations similar to claim 1, and thus, distinguish over the references for similar reasons. Claims 2-8, 10, 11, 13-19, and 21 depend from one of claims 1 and 12, and thus, also distinguish over the references due to their dependency.
Additional searching also turned up WIPO Int’l Pub. No. 2022/125282 A1 to Lee et al. (hereinafter referred to as “Lee”). Lee discloses, “performing claim analysis and generating documents based on the claim analysis from an initial patent, claim, or seed document. For example, systems described herein may perform claim analyses that assist in the evaluation of relative breadth of claims of patents or seed documents as compared to other claims within a collection of patents or documents in a technology area. Additionally, systems described herein may identify products that correspond to elements of one or more claims included in a seed document. Further, systems described herein may identify additional patent documents that correspond to elements of one or more claims included in the seed document” (para. [0015]), “The systems may evaluate a claim by parsing the language in the claim to identify independent concepts, limitations, or claim elements contained within the claim” (para. [0016]), “The systems may also utilize the identified concepts, limitations, or elements to produce one or more search strings that may be used to identify a collection of documents related to a seed document” (para. [0017]), and “The systems may also generate various reports based on the analysis of claims included in patent documents” (para. [0019]), wherein “the patent claim analysis system 102 may re-rank the documents within the collection using a term frequency-inverse document frequency (TF-IDF) technique. Term frequency inverse document frequency is a numerical statistic that is intended to reflect how important a word or term is to a particular document in a collection or corpus. Term frequency-inverse document frequency may be used herein as a weighting factor to assist with ranking the documents within the collection based on the claim elements of the seed document or the one or more search strings. The term frequency-inverse document frequency technique may increase the value of a term proportionally to the number of times a word appears in a document of the collection and is offset by the number of documents in the collection that contain the word, which helps to adjust for the fact that some words appear more frequently in general” (para. [0077]). Thus, while Lee appears to disclose at least some features that appear to read on recited limitations, including the recited “n-gram ratio lift value” limitations (see para. [0077] of Lee) and “document” or “documents” limitations (see Abstract of Lee) of claim 1, Lee does not appear to disclose or suggest generating different document subsets from a set of documents, and further generating further subsets of documents based thereon. As such, Lee fails to disclose or suggest the combination of limitations reproduced above in the discussion of Herath. Claims 12 and 20 recite limitations similar to claim 1, and thus, distinguish over the reference for similar reasons. Claims 2-8, 10, 11, 13-19, and 21 depend from one of claims 1 and 12, and thus, also distinguish over the reference due to their dependency.
Additional searching also turned up ERDURAN, Gamze YILDIZ, and Fatma LORCU. "The investigation of online customer complaints in the banking sector by text mining." Business & Management Studies: An International Journal 8.5 (2020): 3835-3866 (hereinafter referred to as “Erduran”). Erduran discloses, “The fact that banks have a broad customer portfolio leads them to face a large number of online customer complaints. It is imperative to analyse this large amount of online customer complaints data and to evaluate the obtained results by the banking sector. Online customer complaints, which are usually transmitted in text, are large volume, scattered and have complex data structure. To structure this data and discover information from data is a complicated and time-consuming process. Data mining techniques accelerate this process and reveal hidden information within the data set at the same time. Therefore, in this study, customer complaints published by the customers of banks, which have an important place in the economy, on online complaint platforms were analysed by data mining method. In the research, the database created from the original complaint texts expressed by the customers in their own words was grouped using text mining algorithms, and by identifying similar or the words used together, the scope inference of complaints is made” (p. 3839). Like Lee, Erduran also discloses use of TD-IDF in performing analysis (see p. 3846). The results, in Erduran, are metrics about words and phrases (see, e.g., p. 3847-3852). Erduran (like Herath and Lee) does not appear to disclose or suggest generating different document subsets from a set of documents, and further generating further subsets of documents based thereon. As such, Erduran fails to disclose or suggest the combination of limitations reproduced above in the discussion of Herath. Claims 12 and 20 recite limitations similar to claim 1, and thus, distinguish over the reference for similar reasons. Claims 2-8, 10, 11, 13-19, and 21 depend from one of claims 1 and 12, and thus, also distinguish over the reference due to their dependency.
For at least these reasons, pending claims 1-8 and 10-21 appear to distinguish over the prior art of record.
Response to Arguments
On pp. 18-22 of the Amendment, the applicant requests reconsideration and withdrawal of the claim rejection under 35 USC 101. With respect to Step 2A, Prong One of the eligibility analysis, the applicant contends that the Office Action simply provides conclusory statements for every claim element, and general statements that fail to explain why any specific claim language is a certain method of organizing human activity or mental process. (Amendment, pp. 18 and 19.) The examiner disagrees with the contention, at least in part. The assertion of certain methods of organizing human activity has been withdrawn in the 35 USC 101 section above. The examiner contends that the claim language itself reads like mental processes (e.g., thinking about data), and no further explanation is required. Nevertheless, the 35 USC 101 section above provides explanatory examples of mental processes that the claim limitations can cover.
With respect to Step 2A, Prong Two of the eligibility analysis, the applicant contends that the additional elements of the claims being viewed separately from the abstract idea elements is improper. (Amendment, p. 20.) The applicant also contends that there are additional elements that were not considered when making the rejection. (Amendment, pp. 20 and 21.) The examiner agrees in part, and disagrees in part. The examiner agrees that the eligibility analysis requires consideration of the claim as a whole, not consideration of additional elements individually or in a vacuum. The 35 USC 101 section above should be viewed from such a lens. That is, the additional elements are not considered individually or in a vacuum, but are instead considered in combination with each other and the abstract idea elements. The abstract idea elements and the additional elements are only listed separate in the 35 USC 101 section above for clarity. The end result, however, does not change. The additional elements of the claims are nothing more than generic, conventional computer hardware. Their relationship with the abstract idea elements is nothing more than receiving data, processing data, and providing an output, like any generic, conventional computer. The examiner disagrees that the “as a whole” analysis requires the examiner to view abstract idea elements as additional elements, as asserted by the applicant’s footnote (Amendment, pp. 20 and 21). The examiner contends that the abstract idea elements and the additional elements may distinguished from each other, and as long as consideration is given as to how the additional elements relate to the abstract idea elements, and vice versa, requirements are met. With respect to Step 2B of the eligibility analysis, the applicant contends that the claim elements are not well-understood, routine, or conventional, or at least that the Office Action has not properly established that they are. (Amendment, p. 21.) The examiner disagrees with the contention. The claimed “receiving” being performed “by communications hardware,” and the claimed “providing” being performed “by the communications hardware and in real-time” and “to a facility device,” are examples of “Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added))” (MPEP 2106.05(d)(II)(i)). The examiner contends that this alone is sufficient for purposes of making the ineligibility rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Such prior art includes the following:
Wang, Xiaodong, and Juan Wang. "A Method of Hot Topic Detection in Blogs Using N-gram Model." J. Softw. 8.1 (2013): 184-191.
Hussein, Ashraf S. "Visualizing document similarity using n-grams and latent semantic analysis." 2016 SAI computing conference (SAI). IEEE, 2016.
Chen, Maomao, and Maoyi Huang. "Automatic topic extraction from research articles using N-gram analysis." (2016).
Winarko, Edi, and Reza Pulungan. "Trending topics detection of Indonesian tweets using BN-grams and Doc-p." Journal of King Saud University-Computer and Information Sciences 31.2 (2019): 266-274.
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/THOMAS YIH HO/Primary Examiner, Art Unit 3624