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 .
Claim Rejections - 35 USC § 101
Claims 21-40 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim 21
Step 1, this part of the eligibility analysis evaluates whether the claim falls within any statutory category. See MPEP 2106.03. The claim recites a series of steps that performs at least one step. Thus, the claim is to a process, which is one of the statutory categories of invention. (Step 1: YES).
Step 2A, Prong One, this part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim "recites" a judicial exception when the judicial exception is "set forth" or "described" in the claim.
Limitation “matching, by the matching engine, the component values to firmographic data in a production data store using the firmographic data for a partner organization with an association to a source identifier, including applying various rules to determine matches versus non-matches based on similarity”. This limitation recites a judicial exception because it encompasses a mental process. Specifically, comparing pieces of information, evaluating data entries side-by-side, and applying comparison logic to determine similarity are mental steps that can be practically performed entirely within the human mind. For example, a person can manually look at two different company profiles and mentally determine whether there is a match or non-match based on their similarity.
Limitation “wherein a machine learning (ML) model predicts a confidence score for each match”. This limitation recites a judicial exception because it encompasses a mathematical concept. Outputting a numerical "confidence score" represents a mathematical calculation or calculation of probability.
Limitation “retrieving, by the matching engine, a selected source identifier associated with the data in the production data store having a confidence score greater than a threshold score”. This limitation recites a judicial exception because it encompasses a mental process. Specifically, selecting records by determining whether a particular numerical score exceeds a predefined threshold is an evaluation step that can be mentally executed.
"Unless it is clear that a claim recites distinct exceptions, such as a law of nature and an abstract idea, care should be taken not to parse the claim into multiple exceptions, particularly in claims involving abstract ideas." MPEP 2106.04, subsection II.B. However, if possible, the examiner should consider the limitations together as a single abstract idea rather than as a plurality of separate abstract ideas to be analyzed individually. "For example, in a claim that includes a series of steps that recite mental steps as well as a mathematical calculation, an examiner should identify the claim as reciting both a mental process and a mathematical concept for Step 2A, Prong One to make the analysis clear on the record." MPEP 2106.04, subsection II.B. Here, the mentioned steps fall within the Mental Processes and Mathematical Concepts groupings of abstract ideas and are considered together as a single abstract idea for further analysis. (Step 2A, Prong One: YES).
Step 2A, Prong Two, the claim recites the additional elements:
An interface of a matching platform
A receiving data store of the matching platform
A matching engine
A production data store
A user device in operative communication with the matching platform
Receiving ambiguous firmographic data as a data object in a native file format
Persisting the ambiguous firmographic data as a data object in native format
Providing the ambiguous firmographic data as input
Formatting the data object into an acceptable format by parsing it to delineate component values, and transforming it into a parquet format aligned/normalized with data types within a relevant input schema
Providing a selected source identifier as a lookup key to query the production data store to a user device
MPEP § 2106.05(a) Improvements to the Functioning of a Computer or to Any Other Technology or Technical Field.
The additional limitations of receiving data, parsing it, converting it to a "parquet format aligned, or normalized with, data types within a relevant input schema", and querying databases using standard generic computers, generic matching engines, and data stores do not improve the functioning of the computer itself or any other technology. It merely leverages existing digital storage formats (like Parquet) and standard processing operation to process information. The additional elements do not an improvement to an underlying hardware or technological technical field.
MPEP § 2106.05(b) Particular Machine.
The generic computer components: the “interface," "matching platform," "receiving data store," "matching engine," "production data store," and "user device" do not constitute a particular machine.
MPEP § 2106.05(c) Particular Transformation.
The parsing and transformation of firmographic data objects into a "parquet format" does not constitute a transformation of a physical article into a different state or thing. It merely changes the digital formatting.
MPEP § 2106.05(e) Other Meaningful Limitations.
The additional elements do not place meaningful limitations on the abstract concept. They just describe normal everyday data operations. Converting files into standard data schemas and running them through common machine models can be done on any standard database infrastructure. Because these steps can be used so broadly, they fail to narrow the claim down to a specific technological application.
MPEP § 2106.05(g) Insignificant Extra-Solution Activity.
The steps of "receiving ambiguous firmographic data" at the beginning of the method and "providing the selected source identifier... to a user device" are insignificant extra-solution activities. Pre-solution data gathering (ingesting data) and post-solution data delivery (transmitting a lookup key to a user device screen or log file) are pre-post solution activities
MPEP § 2106.05(h) Field of Use and Technological Environment.
[T]he Supreme Court has stated that, even if a claim does not wholly pre-empt an abstract idea, it still will not be limited meaningfully if it contains only insignificant or token pre- or post-solution activity-such as identifying a relevant audience, a category of use, field of use, or technological environment. Ultramercial, Inc. v. Hulu, LLC, 722 F.3d 1335, 1346 (Fed. Cir. 2013). Limitations “matching platform”, “interface’, “ambiguous data”, “a receiving data store”, “native file format”, “firmographic data”, “matching engine”, “source identifier”, “user device” are simply a field of use that attempts to limit the abstract idea to a particular technological environment.
Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Examining the elements of the independent claim, both individually and as an ordered combination, to see if they provide an inventive concept reveals that the claim limits do not describe a specific, non-generic solution to a specific technical problem, but rather rely entirely on conventional practices. The ordered arrangement of ingesting raw data, saving it, parsing it into component values, mapping it to a schema, running similarity checks, and returning an identifier consists of highly conventional data-processing operations in the database administration field. Using Parquet formatting or confidence scoring via generic computer systems performs routine data manipulation faster but does not make the combination to "significantly more." Therefore, the claim does not amount to significantly more than the recited abstract idea, and the claim is not patent eligible.
Claim 23 depends on claim 21 and includes all the limitations of claim 21. Claim 23 recites “wherein the ambiguous data is received from a business store.” The claim does not have any addition limitation that amount to significantly more than the abstract idea.
Claim 24 depends on claim 21 and includes all the limitations of claim 21. Claim 24 recites “wherein the ambiguous data is received via an event streaming platform.” The claim does not have any addition limitation that amount to significantly more than the abstract idea.
Claim 25 depends on claim 21 and includes all the limitations of claim 21. Claim 25 recites “wherein matching comprises a minhash to create a similarity score for firmographic fields of the firmographic data. The minhash is recited at a high level of generality. The claim does not have any addition limitation that amount to significantly more than the abstract idea.
Claim 26 depends on claim 21 and includes all the limitations of claim 21. Claim 26 recites “wherein matching comprises a vector multiplication to create a similarity score for firmographic fields of the firmographic data.” The vector multiplication is recited at a high level of generality. The claim does not have any addition limitation that amount to significantly more than the abstract idea.
Claim 27 depends on claim 21 and includes all the limitations of claim 21. Claim 27 recites “wherein the matching engine includes a machine learning model” The machine learning model is recited at a high level of generality. The claim does not have any addition limitation that amount to significantly more than the abstract idea.
Claims 28, 30-35, and 37-40 are similar to claims 21, 23-27. The claims are rejected based on the same reasons.
Claim 29 depends on claim 28 and includes all the limitations of claim 28. Claim 29 recites “wherein the ambiguous data is firmographic data.” The claim does not have any addition limitation that amount to significantly more than the abstract idea. Claim 36 is similar to claim 29. The claim is rejected based on the same reason.
Response to Arguments
Section B – Claim Rejections Under 35 U.S.C. 101 – pg 9-10
Applicant argues “Under Step 2A, Prong One, the amended claims should not be characterized at a high level as merely "matching" data. The claims require operations tied to computer data structures, native-format data objects, schema alignment, similarity scoring, ML-based confidence scoring, and production data-store lookup keys. These operations are not practically performable as a mental process because the claims require computer processing of native-format data objects and schema- normalized component values across a matching platform and production data store…”
Applicant’s arguments have been considered but are found unpersuasive. Applicant argues that the claims are not directed to a mental process because they require operations "tied to computer data structures, native-format data objects, schema alignment, similarity scoring, ML-based confidence scoring, and production data-store lookup keys." Applicant further argues that these steps are "not practically performable as a mental process" because they require automated processing across a matching platform. Examiner respectfully disagrees because the core underlying concepts of "matching data entries" and "applying rules to determine similarity" remain logical evaluations that can be conceptually performed in the human mind. Furthermore, generating "confidence scores" using a machine learning model relies fundamentally on calculations, which fall within the Mathematical Concepts grouping.
Applicant argues that “Under Step 2A, Prong Two, even if the Office were to identify some alleged abstract concept within the claims, the additional claim elements integrate any such concept into a practical application. The specification explains that conventional queries using ambiguous data were inefficient in terms of both human and technological resources, and that the disclosed platform processes ambiguous firmographic data to identify a source identifier usable to query a production data store for partner-organization data. See paragraphs [0002], [0027], [0030], [0041]- [0046], and [0054]. The claimed native-format ingestion, parsing, schema normalization, similarity-rule processing, ML confidence scoring, and source- identifier lookup output provide a concrete technological implementation for resolving ambiguous firmographic data within a matching platform.
For similar reasons, the amended claims recite significantly more under Step 2B. The ordered combination is not generic receipt, storage, comparison, and display of data. It is a particular arrangement in which ambiguous firmographic data is preserved as a native-format data object, converted into component values aligned or normalized with an input schema, scored by similarity-based rules and an ML model, and used to select a source identifier that functions as a lookup key for production data. Accordingly, Applicant respectfully requests withdrawal of the § 101 rejection of claims 21-40…”
Applicant argues that the claims integrate the abstract ideas into a practical application because the specification notes that conventional queries using ambiguous data were "inefficient in terms of both human and technological resources." Applicant argues that the claimed pipeline provides a concrete technological implementation for resolving this resource inefficiency. To prove a real technical improvement under patent law, the specific solution must be written directly into the claim steps. It is not enough to just write about the desired benefits in the background of the patent description. The steps-like receiving data, running machine learning calculations, and pulling a standard identifier - just use ordinary computer storage and standard database equipment. Merely using a regular computer to perform a mental comparison or a math calculation faster does not improve the computer's underlying technology. Instead, it just optimizes the abstract idea itself.
Suggestion
Claim 21 A method comprising:
receiving ambiguous firmographic data at an interface of a matching platform, wherein the ambiguous firmographic data is received as a data object in a native file format;
persisting the ambiguous firmographic data, as the data object in a native format, to a receiving data store of the matching platform, wherein the receiving data store is configured as a data lake or key-value store to store the data object with embedded schema information;
providing the ambiguous firmographic data, as the data object, as input to a matching engine, wherein the matching engine formats the data object into an acceptable format by parsing the data object to delineate each value as a component value, and transforming the ambiguous firmographic data into a parquet format and aligned, or normalized with, data types within an relevant input schema;
matching, by the matching engine, the component values to firmographic data in a production data store using the firmographic data for a partner organization with an association to a source identifier, including applying various rules to determine matches versus non-matches based on similarity, wherein a machine learning (ML) model predicts a confidence score for each match, wherein the machine learning (ML) model performs cleansing operations to normalize fields and create similarity scores for firmographic fields;
wherein when the data object is missing a number of firmographic elements used for matching, a thin record indicator is used to focus a match rule on a particular firmographic element that does exist within the data object, including focusing on URL matches in the same country if other firmographic elements are not available;
retrieving, by the matching engine, a selected source identifier associated with the data in the production data store having a confidence score greater than a threshold score; and
providing the selected source identifier, as a lookup key to query the production data store for data/objects related to the partner organization, to a user device in operative communication with the matching platform.
Section C – Claim Rejections Under 35 U.S.C. 103
The rejections to claims 21-40 are withdrawn as necessitated by Amendment.
Conclusion
THIS ACTION IS MADE FINAL. 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.
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.
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HAU HAI. HOANG
Primary Examiner
Art Unit 2154
/HAU H HOANG/ Primary Examiner, Art Unit 2154
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