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 05/15/2023.
Claims 1 – 20 are currently pending.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 05/15/2023 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, 14 includes the following limitations that directed to an abstract idea:
“generating, by a computer, a dimension score for each respective dimension of a plurality of predefined dimensions as relating to column attributes of a data asset while performing a static reference data analysis of the data asset”, as drafted, recites a mentally process as an evaluation or judgement. Scoring attributes based on predefined dimensions is a process that could be performed by a human, and simply "automating" this on a general-purpose computer does not remove the abstract nature. This is also
consistent with the specification as in Para. 0044 of the Disclosure, where one can
mentally “sets a score for each respective row of a dimension table corresponding to that particular dimension … then illustrative embodiments assign the score corresponding to that row to the data asset”.
“adding, by the computer, the dimension score of each respective dimension together to obtain a total dimension score for the data asset”, as drafted, recites a mentally process as an evaluation or judgement. Adding or aggregating numbers (scores) to obtain a total score falls under the category of a mathematical concept or a method of organizing human activity. This is also consistent with the specification as in Para. 0045 of the Disclosure, where one can mentally “determine the final total dimension score for the data asset by summing the total scores of all the dimensions corresponding to the data asset”.
“determining, by the computer, whether the total dimension score of the data asset is greater than a predefined minimum dimension score threshold level” as drafted, recites a mentally process as an evaluation or judgement. A user can mentally perform the logic of checking if a score exceeds a minimum threshold using a pen and paper. In addition, comparing two numbers (a score versus a threshold) is a fundamental mathematical operation. This is also consistent with the specification as in Para. 0045 of the Disclosure, where one can “determine whether the final total dimension score of the data asset is greater than a predefined minimum dimension score threshold level”.
“identifying, by the computer, the data asset as new static reference data in response to the computer determining that the total dimension score of the data asset is greater than the predefined minimum dimension score threshold level”, as drafted, recites a mentally process as an evaluation or judgement. A user can mentally could look at a data asset, score its dimensions, check a minimum threshold, and sort it into a "static reference data" pile. Further, calculating scores and checking if they exceed a mathematical threshold falls under mathematical relationships. (See Electric Power Group, LLC v. Alstom S.A., where the Federal Circuit held that collecting, analyzing, and displaying information is abstract.)
“generating, by the computer, a new data class based on the new static reference data”, as drafted, recites a mentally process as an evaluation or judgement. A user can mentally judge/evaluation the received data and structuring data into a new "class" based on existing "reference data". Because these cognitive processes can be performed in the human mind or with pen and paper, they are considered abstract ideas.
Step 2A, Prong Two:
The claim recites no additional elements. At most one might consider that a "storage device, processor executes the program instructions…" as claimed might be considered to represent a computer-implemented consistent with Fig. 1. At most this would be a high-level recitation of a generic computer components and represents mere instructions to apply the abstract idea on a computer as in MPEP 2106.05(f), which 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 " storage device, processor executes the program instructions…" 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 includes “receiving, by the computer, an input to perform a data classification analysis on the data asset; retrieving, by the computer, a plurality of existing data classes and a plurality of existing static reference data; retrieving, by the computer, the plurality of predefined dimensions; and retrieving, by the computer, the data asset to perform the data classification analysis on the data asset”, as drafted this recites a mentally performable process as an evaluation or judgement. One can mentally judge/evaluation receiving inputs, retrieving information (existing data classes, static reference data, and predefined dimensions), and performing an analysis. Under its broadest reasonable interpretation when read in light of the specification, this limitation is recited at a high level of generality, can be performed by human mind, which is a form of metal activity. See MPEP 2106.04(a)(2), subsection III.
The dependent claims 3 - 4 includes “selecting, by the computer, a column from a set of columns of the data asset; applying, by the computer, each of the plurality of existing data classes to the column one by one; and determining, by the computer, whether a match exists between the column and a data class of the plurality of existing data classes”, “classifying, by the computer, the column of the data asset utilizing the data class of the plurality of existing data classes that matches the column; and returning, by the computer, the data class that matches the column of the data asset”, as drafted this recites a mentally performable process. The actions of looking at a set of data, reviewing individual columns, comparing the contents to known categories (like checking if data looks like an address or a name), and determining if there is a match is a routine cognitive task that humans have historically performed manually. See MPEP 2106.04(a)(2), subsection III.
The dependent claims 5 - 6 includes “identifying, …in response to the computer determining that a match does not exist … performing, … a comparison between the values …and determining, …”, “classifying… returning …”, as drafted this recites a mentally performable process. The claim outlines a basic logical process of cross-referencing information (identifying, comparison, determining) is mental concept that humans can perform manually or using a pen and paper. (See Electric Power Group v. Alstom case law).
The dependent claims 7 includes “performing, by the computer, the static reference data analysis of the data asset in response to the computer determining that …”, as drafted, recites a mentally process as an evaluation or judgement. Because a human could theoretically perform this task using a pen, paper, and a reference ledger, it is legally treated as a "mental process" automated by a machine.
The dependent claims 8 - 9 includes “returning, by the computer, the data asset for manual data classification in response to the computer determining that the total dimension score of the data asset is not greater than the predefined minimum dimension score threshold level”, “linking, by the computer, the new static reference data to the new data class” as drafted, recites a mentally process as an evaluation or judgement. Determining a score and comparing it to a threshold is essentially a mental calculation. The acts of performing a basic mathematical comparison, and linking it to a category, in your head or on paper is a fundamental "abstract idea."
The dependent claims 10 includes “wherein the plurality of predefined dimensions includes a columns count dimension that represents a total number of columns in the data asset, a distinct columns count dimension that represents a number of columns having distinct values in the data asset, a columns named key dimension that represents a number of columns named key in the data asset, a key columns value length dimension that represents a percentage of values having a same length in the columns named key in the data asset, and a key columns value format dimension that represents a percentage of values having a same format in the columns named key in the data asset”, as drafted, recites a mentally process as an evaluation or judgement. The steps involve counting columns, identifying distinct values, and calculating percentages of values having the same format or length. The Acts of collecting data, analyzing it, and categorizing metrics using basic mathematical concepts can be performed entirely in the human mind. Because a human could theoretically perform this task using a pen, paper, and a reference ledger, it is legally treated as a "mental process" automated by a machine.
Claims 11 - 20, Applicant claims the abstract idea on a system with processors and instructions 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 "generating … adding… determining… identifying… generating…" 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:
Segev et al (U.S. 2024/0126918 A1) discloses a method, system for data classification including the teaching of “A classifier is applied to features extracted from the second sample, where each classifier is a machine learning model trained to output a second score representing a likelihood for a respective classification for each of the second sample. A set of classifications are determined based on the first score and the second score” (See abstract).
Neerju et al (US 20210294817 A1) discloses a method of data classification includes: identifying a cluster of data classes; classifying columns of a current data set; identifying the cluster in the current data set; determining, based on the cluster, an expected column is missing from the current data set; determining a neighboring data set; identifying the expected column in the neighboring data set; classifying the expected column in the neighboring data set; creating a new data class in the current data set; and classifying an unclassified column in the current data set or the neighboring data set with the new data class (See abstract).
Winzenried et al (U.S. 20200034479 A1) discloses a classifier system and method including the teaching of “the results generated and output at various steps of routine 200 can be scored in one or more dimensions” (Para. 0059, Fig. 2).
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, or camlinh.nguyen@uspto.gov . 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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