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 .
This Office Action is responsive to communication filed on 04/22/2025.
Claims 1 – 20 are currently pending.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/11/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 – 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 - 20 are directed to a "method and system, and product", and therefore, directed to a statutory category.
Step 2A, Prong One:
The independent claims 1, 11, includes the following limitations that directed to an abstract idea:
“determining, by the computer system, a combination method to combine at least two datasets of the plurality of datasets” as drafted, recites a mentally process as an evaluation or judgement. One can mentally determine which is the best method to combine datasets. This is also consistent with the Disclosure, Para. 0101 wherein the user can identify a combination method such as join combination of two given data assets.
“identifying, by the computer system and using the combination method, a subset of each determined dataset” as drafted, recites a mentally process as an evaluation or judgement. One can mentally determine a subset of the datasets. This is also consistent with the Disclosure, Para. 0104 wherein the user can identify a subset of data for joining the datasets.
“determining, by the computer system, a composite score for each subset and each dataset of the at least two datasets, wherein the composite score is calculated based on information characteristics, meaning characteristics, and a size of each subset or dataset” as drafted, recites a mentally process as an evaluation or judgement. The act of “calculating” a composite score is categorized as mathematical process. One can mentally judge/evaluate the meaning characteristic of data, the size of the data, and calculate the score. This is also consistent with the Disclosure, Para. 0105 wherein the DIM value for the dataset is determined.
“combining, by the computer system, each subset according to the combination method selected” as drafted, recites a mentally process as an evaluation or judgement. The act of “combining” each subset is categorized as mental process, such as merging data or manipulation data which can be performed in human mind of with a pen and paper. This is also consistent with Para. 0106 of the Disclosure wherein one can combine subsets subA and subB using the identified combination method and generate the combined dataset (e.g., datasetC).
“determining, by the computer system, a composite score for the combined subsets, wherein the composite score is calculated based on the information characteristics, the meaning characteristics, and the size of the combined subsets” as drafted, recites a mentally process as an evaluation or judgement. The act of “calculating” a composite score is categorized as mathematical process. One can mentally judge/evaluate the meaning characteristic of data, the size of the data, and calculate the score. This is also consistent with the Disclosure, Para. 0107 wherein the DIM value for the dataset is determined.
“determining, by the computer system, whether the composite score of the combined subsets satisfies a condition in relation to addition of the composite scores of each dataset of the at least two datasets” as drafted, recites a mentally process as an evaluation or judgement. One can mentally judge/evaluate the composite score, compare it with a condition. Comparing a composite score to another value falls under concepts that can be performed entirely in the human mind using a pen and paper. This is also consistent with the Disclosure, Para. 0108 wherein one can determine whether the DIM value of dimC is greater than the sum of dimA and dimB.
“performing, by the computer system, an operation based on whether or not the condition is satisfied” as drafted, recites a mentally process as an evaluation or judgement. One can mentally judge/evaluate the condition is satisfied or not then perform an action accordingly.
Step 2A, Prong Two:
The claim recites additional elements such as:
That the method is processed by "computer system", which is a high-level recitation of a 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.
“receiving, by a computer system, a plurality of datasets, each of the plurality of datasets comprising a plurality of data” is insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' and the particulars of the retrieved data are merely "selecting information … for collection, analysis, and display" as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application
Step 2B
The claims do not include additional elements that are sufficient to amount to
significantly more than the judicial exception.
In this case, the "receiving… data set…", “by a computer system” are identified as insignificant extra-solution activity above when re-evaluated these elements are well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II),' "i. 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); "computer-implemented", and performed by "one or more
processors", a system includes memory storing instruction coupled to a processor,
are considered insignificant extra- solution activity, and do not take the claim limitations out of the mental processes grouping. See MPEP - 2106.05(g) ("whether the limitation is significant").
Accordingly, the additional limitations are not providing significantly more than the
judicial exception. Looking at the claim as a whole does not change this conclusion and
therefore, the claim is ineligible.
The dependent claims 2 – 3, 12 - 13 includes “determining a lift of the plurality of datasets prior to determining a composite score for the combined subsets, wherein the lift measures a value of non-linearity in combination of the combined subsets”, “wherein the determining the lift is in response to determining that a number of datasets of the plurality of datasets satisfies a threshold”, as drafted this recites a mentally performable process as an evaluation or judgement. The act of analyzing relationships between datasets in order to measure a value is considered a mental process that can be performed entirely in the human mind or with a basic generic processor. Evaluating, or measuring combinations of data using "lift" and "non-linearity" is considered a mathematical relationship/formula. Comparing a data count to a "threshold" is a mental process, even if performed on a computer. See Alice v. CLS Bank.
The dependent claims 4 – 5, 14 - 15 includes “wherein the determining the composite score of the combined subsets or the determining the composite score for each of the subsets includes: extracting, using a regression and classification machine learning algorithm, metadata from the subset or the combined subsets; creating, using the regression and classification machine learning algorithm, a metadata extracted object that is associated with each subset or the combined subset; creating a first sub-score for each subset or the combined subset, the first sub-score comprising a first numerical value, the first numerical value being larger for datasets with more data; creating a second sub-score for each subset or the combined subset, the second sub-score comprising a second numerical value, the second numerical value varying based on information characteristics, the second sub-score being larger for improved information characteristics, wherein improved information characteristics are characterized by increased structural quality, increased completeness, increased interconnectivity, increased diversity, and decreased redundancy, and wherein the information characteristics are determined in least in part from the metadata extracted object; creating a third sub-score for each subset or the combined subset, the third sub-score comprising a third numerical value, the third numerical value varying based on meaning characteristics, the third sub-score being larger for improved meaning characteristics, wherein improved meaning characteristics are characterized by increased impact on a community, an increased number of impacted communities, greater veracity, greater relevance to an impacted community, greater scarcity, higher validity, lower veracity decay, and increased users within a community, and wherein the meaning characteristics are determined in least in part from the metadata extracted object; creating the composite score for each subset or the combined subset that is a mathematical combination of the first sub-score, the second sub-score, and the third sub-score”, as drafted this recites a mentally performable process. The actions of creating a composite score that is a "mathematical combination of the first sub-score, the second sub-score, and the third sub-score" is essentially an algorithmic calculation. Merely using "a regression and classification machine learning algorithm" to extract metadata and perform a calculation typically is viewed as a generic technological tool to execute the math.
The dependent claims 6 – 9, 16 - 19 includes “appending a certification of the composite score to each of the datasets, wherein the certification includes pointers to the dataset, the metadata extracted object for that dataset, and the composite score; wherein the second sub-score further comprises a scoring of interconnectivity between data within a dataset, such scoring being a non-linear function, wherein zero interrelatedness of data and complete interrelatedness of data score a lower score than partial interrelatedness of data; wherein the second sub-score is scored by the computer system using artificial intelligence or machine learning, wherein the artificial intelligence or machine learning was trained on already scored and corrected datasets”, as drafted this recites a mentally performable process. Creating a certification that includes pointers, metadata, and a composite score is a well-known method of organizing, tracking, and displaying information. The use of a "non-linear function" to determine interconnectivity is a mathematical formula. And finally, the act of evaluating the "interrelatedness" of data is an analytical task that humans can be performed or using pen and paper.
The dependent claims 10, 20 includes “empirically adjusting one or more of the first sub-score, the second sub-score, or the third sub-score by adding or deleting data; creating an adjusted composite score from the empirically adjusted one or more of the first sub-score, the second sub-score, or the third sub-score”, as drafted, recites a mentally process as an evaluation or judgement. Calculating, adjusting, or evaluating sub-scores is implemented as a mathematical, mental, or computerized process, making it a mathematical concept.
Claims 11 - 20, Applicant claims the abstract idea on a tangible, non-transitory, machine readable medium with instructions executed by processors to carry-out the method as in claim 1, without adding further limitations that amount to more than generally linking the use of the exception to a particular technological environment. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. The use of generic computer components to "receiving…determining…performing an operation" do not impose any meaningful limit on the computer implementation of the abstract idea. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea).
Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. The claims are not patent eligible.
The following are some related arts:
Kumar et al (US 20240176788 A1) discloses a method implements a dataset rank metric for measuring dataset relevance including the teaching of “A composite score is generated for each node of the graph. The computer processor iteratively processes the composite scores for the multitude of nodes of the graph to generate a dataset rank for each dataset” (See abstract, Fig. 2, 4 and associated texts of Kumar).
Herrera et al (US 20220164374 A1) discloses creating a composite score for each of the plurality of datasets that is a mathematical combination of the first, second, and third sub-scores (abstract, Para. 0095, 0105).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAM LINH T NGUYEN whose telephone number is (571)272-4024. The examiner can normally be reached M-F: 7:00 - 3:00 pm.
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/CAM LINH T NGUYEN/Primary Examiner, Art Unit 2161
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