DETAILED ACTION
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 9/24/2025 has been entered. Claims 1-3, 5-9, 11-17, and 19-20 are pending in the application.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/3/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Applicant's arguments filed 9/24/2025 have been fully considered.
Regarding the arguments 1-2 on pages 12-19 including “The pending claims are patent eligible in line with the Memorandum from the USPTO, dated August 04, 2025” that “unpatentability must be established by a preponderance of the evidence” and “The Claims do not recite an abstract idea under Step 2A -Prong One”, examiner respectfully disagrees.
As explained in MPEP 2106.04(I), “even newly discovered or novel judicial exceptions are still exceptions. … Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 714-15, 112 USPQ2d 1750, 1753-54 (Fed. Cir. 2014). Cf. Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016) ("a new abstract idea is still an abstract idea") (emphasis in original). Similarly, as stated in MPEP 2106.05(a), discussing the improvements consideration states, “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements.” A new or improved abstract idea is still an abstract idea. The programmed computer or "special purpose computer" test of In re Alappat, 33 F.3d 1526, 31 USPQ2d 1545 (Fed. Cir. 1994) (i.e., the rationale that an otherwise ineligible algorithm or software could be made patent-eligible by merely adding a generic computer to the claim for the "special purpose" of executing the algorithm or software) was also superseded by the Supreme Court’s Bilski and Alice Corp. decisions.
The limitation “using a processor that tracks in computer memory” is not tracking memory usage, and is still counting the number of queries received, which is mentally performable. This sort of construction is nothing more than “apply it” (the abstract idea) on a computer. The fact this ‘counting’ is performed “using a processor” that keeps the count (i.e. tracks this) “in computer memory” does not make it not mentally performable.
The “determined” steps are merely done “using the processor” and tracking the counts “in computer memory.” This is not inextricably tied to what is being counted being related to the processor or memory – it is merely claimed as done using those as a tool. Per MPEP 2106.05(f), this is the quintessential “apply it” consideration and does not provide integration into a practical application or significantly more.
The same also applies for the amendments to “a decision tree … generating a set of nodes in computer memory” and “navigating in computer memory from a root note … to another node.” Taking the original appeal decision into consideration, they were clear that generating a schedule by navigating the decision tree was a mental process. Merely claiming that this mental tree is stored in memory is not anything more than apply it on a computer. There is nothing in the claim that indicates this is more than the mental process, but just with the data held in computer memory. The nodes have no specific relationship to the computer memory, and the navigating the nodes in memory is not a function that is inextricably tied to the computer memory such that it would not be mentally performable. Note that this is not saying the computer memory itself is organized as a set of nodes in a decision tree or the like, just that computer memory holds this information – which the PTAB already said is practically held and navigated mentally. Please see explanations below.
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, 5-9, 11-17, and 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claims 1-3, 5-9, 11-17, and 19-20 fall within the statutory category of a process and an apparatus or system.
Step 2A, Prong One: the claim recites a Judicial Exception.
Claim 1 recites “modifying an asset addition operation of a knowledge base system…an efficient decision tree comprising a set of nodes in computer memory used in the knowledge base system such that a timing of asset addition into the knowledge base system is optimized relative to a timing of an expected query regarding the added asset, by” is a mental evaluation or judgement of modifying an asset addition operation to a knowledge base system which can be performed in a human mind. Based on certain periods of time, e.g., in winter certain supplies are needed in greater amount/number or in each August at the beginning of a school year, school supplies are needed more for students etc. Thus, modifying an asset addition operation of a knowledge base system is mentally performable. And therefore, the steps fall within the mental processes grouping.
The two steps of “constructing, for a first query classification, a query time series, …”, “constructing, for a first asset classification, a topic time series, …” and the other two steps recite “generating” a decision tree from the time series and “generating” a schedule by navigating operation on the decision tree can be performed in the human mind with the use of pen and paper. The limitation “in computer memory” is not tracking memory usage, and is still counting the number of queries received, which is mentally performable. This sort of construction is nothing more than “apply it” (the abstract idea) on a computer. The fact this ‘counting’ is performed “using a processor” that keeps the count (i.e. tracks this) “in computer memory” does not make it not mentally performable. And thus, the steps fall within the mental processes grouping which recites an abstract idea. See MPEP § 2106.04(a)(2)(III).
In addition, the “determined” steps are merely done “using the processor” and tracking the counts “in computer memory.” Again, this is not inextricably tied to what is being counted being related to the processor or memory – it is merely claimed as done using those as a tool. Per MPEP 2106.05(f), this is the quintessential “apply it” consideration and does not provide integration into a practical application or significantly more. The same also applies for the amendments to “a decision tree … generating a set of nodes in computer memory” and “navigating in computer memory from a root note … to another node.” Taking the original appeal decision into consideration, they were clear that generating a schedule by navigating the decision tree was a mental process. Merely claiming that this mental tree is stored in memory is not anything more than apply it on a computer. There is nothing in the claim that indicates this is more than the mental process, but just with the data held in computer memory. The nodes have no specific relationship to the computer memory, and the navigating the nodes in memory is not a function that is inextricably tied to the computer memory such that it would not be mentally performable. Note that this is not saying the computer memory itself is organized as a set of nodes in a decision tree or the like, just that computer memory holds this information – which the PTAB already said is practically held and navigated mentally.
The steps of “modelling, by having a first program instruction interact with the knowledge base system to cause a fitting of the query time series and the topic time series to a forecasting model, the query time series and the topic time series; interacting with the knowledge base system via a second program instruction to cause an identifying operation, using the forecasting model, of a set of variables contributing to a seasonal variation in the query time series and the topic time series” is a mental process as an evaluation or judgement, mathematical relationships/concepts.
As stated in the PTAB decision, both of the “constructing” limitations and the “generating” limitations recite mental processes. While the final two generating limitations have been amended on 3/1/2024 to recite further details of the variables and specifics of the content of the “decision tree” and “schedule”, these limitations still appear to recite mental processes since under its broadest reasonable interpretation, covers performance of the limitations in the mind. One can still mentally generate the claimed decision tree and mentally generate the claimed schedule – the same as PTAB found.
In addition, the step: “modelling”, “a fitting of the query time series and the topic time series to a forecasting model” is a long-existing modeling technique that has been used in forecasting various problems and generally such modeling can be done manually in a non-automated fashion. Accordingly, this claimed “modelling” limitation appears to recite a mentally performable process, as one can mentally with pen and paper.
As noted in the PTAB decision dated 2/2/2024, page 9, last paragraph, even if performing this mentally/manually is time consuming, “relying on a computer to perform routine tasks more quickly or more accurately is insufficient to render a claim patent eligible”. (Citing Alice, 573 U.S. at 224 ("use of a computer to create electronic records, track multiple transactions, and issue simultaneous instructions" is not an inventive concept)).
Each claimed step can be performed in the human mind, with or without the use of a physical aid such as pen and paper, and thus the steps fall within the mental processes grouping and mathematical concepts, thus, claim 1 recites an abstract idea. See MPEP § 2106.04(a)(2)(III). Independent claims 7 and 15 recite limitations of commensurate scope. For the reasons stated above for claim 1, claims 7 and 15 also recite mental processes, mathematical concepts groupings of abstract ideas.
Step 2A, Prong Two: exception is not integrated into a practical application.
The claims recite the additional elements "a computer usable program product," "computer readable storage devices," "program instructions", "a computer system" "processors," "computer-readable memories," "computer-readable storage devices," and "program instructions" which are high-level recitation of generic computer components and represents mere instructions to apply on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application. Thus, none of these additional elements would render the claim eligible. Viewing the additional limitations together and the claims as a whole, nothing provides integration into a practical application.
Step 2B: “Inventive Concept” or “Significantly More”
The claim recites generic computer components (e.g., “a processing device”, “a memory device”, “one or more computer- readable storage devices”, and “program instructions”, and “a computer system”, “one or more processors”, “one or more computer-readable memories” (in claims 7 and 15) performing generic computing functions or generic computer components and represents mere instructions to apply on a computer as in MPEP 2106.05(f). Therefore, the recited generic computing functions or components do not provide significantly more and the claim as a whole does not change the conclusion. In addition, based on the forecasting results, certain assets are needed/be used in the future time/seasons, said assets are added in the knowledge base/knowledge assets. See MPEP § 2106.05(d). Accordingly, the claimed limitations recited above are abstract ideas under mental processes
and the claims 1, 7 and 15 are ineligible.
Claims 2-3, 5-6, 8-9, 11-14, 16-17, and 19-20 add further limitations which are also directed to an abstract idea. The claims recite steps of “classifying, using a Natural Language Understanding model, a first natural language query into the first query classification”; “classifying, using a Natural Language Understanding model, a first knowledge asset into the first asset classification”, “generating, for a natural language query in the first query classification, an over-specified query, the over-specified query specifying a subset of information requested by the natural language query; and generating, responsive to determining that a first result of applying the natural language query to the set of knowledge assets and a second result of applying the over-specified query to the set of knowledge assets are within a threshold similarity to each other, a revised schedule, the revised schedule forecasting a time at which a knowledge asset identified using the similarity between the over-specified query and the natural language query should be added to the set of knowledge assets”, “generating, for a natural language query in the first query classification, an under- specified query, the under-specified query specifying a superset of information requested by the natural language query; and generating, responsive to determining that a first result of applying the natural language query to the set of knowledge assets and a second result of applying the under-specified query to the set of knowledge assets are within a threshold similarity to each other, a revised schedule, the revised schedule forecasting a time at which a knowledge asset identified using the similarity between the under-specified query and the natural language query should be added to the set of knowledge assets”.
Said claims can be performed using human mental evaluation or judgement, and fall into the abstract idea of a mental process, similar to the independent claims. Because the additional elements do not impose meaningful limitations on the judicial exception and the additional elements are well-understood, routine and conventional functionalities in the art, the claims are directed to an abstract idea and are not patent eligible.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Chen et al. (US 8126839) teaches at col. 6:22-24: boosted trees are a series of decision trees, which may be denoted by h.sub.i(x). A prediction function may be based on these decision trees.
Koh (US 20170178229) teaches in para. 21: the actual volume data 2 and client historical volume data 1 act as input into the forecasting module 110, i.e. for applying a time series analysis model for volume forecasting using the statistical module.
Cox (US 20170235894) teaches in para. 244: “Model selection may include models that remove seasonal and irregular variations in observable values. Body Mass Index (BMI) may be expected to increase in the winter and decrease in the summer, for example, while we do not expect seasonal variations in blood pressure. Trend slope and confidence levels and projections for future measurements can be calculated using a wide range of mathematical models. Available models for trend analysis include least squares fit model, iteratively weighted least squares model, generalized linear model (GLM), and autoregressive integrated moving average (ARIMA) models”.
Anderson et al. (US 20150317589) teaches at para. 168: various ML models such as, for example, Artificial Neural Networks (ANN), tree classification, Bayesian Additive Regression Trees (BART), Support Vector Regression (SVR) and time series methods such as variants of SARIMA, can be deployed to forecast the load profile. In this exemplary application, each of these models was tested and the SVR model provided the best load forecasting results. Pan (US 20140114556) teaches at para. 34-35: ARIMA forecasting model and decision trees.
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/LINH BLACK/Examiner, Art Unit 2163 1/8/2026
/TONY MAHMOUDI/Supervisory Patent Examiner, Art Unit 2163