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 Non Final office action is in response to Applicant’s communication received December 27, 2024. Claims 1-20 are pending and under examination.
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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Subject Matter Eligibility Standard
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter.
Specifically, claim 1 is directed to a method. Claims 17 is directed to a system claim. Each of the claims falls under one of the four statutory classes of invention.
If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea).
Under Step 1 of the analysis, claim 1 is directed to a method claim. Claim 17 is directed to a system. The claims fall under one of the four statutory classes of invention under step 1.
Representative claim 1 recites the limitations in the abstract idea highlighted in non-bold and the “additional elements” in bold below.
providing a user transactional behavior dataset by a processor, the user transactional behavior dataset including:
a plurality of user transactional behavior data elements collected by a system, each of the plurality of user transactional behavior data elements including one or more feature attributes;
generating, using the processor, a first sub-dataset in a first data storage layer of the multi-layered data storage system, the first sub-dataset narrowed to user transactional behavior data elements including one or more user-requested feature attributes requested by a first user;
calculating, using the processor, approximate feature attributes of the first sub-dataset, based on one or more adjusted feature attributes;
generating, using the processor, a second sub-dataset, wherein the second sub-dataset is formed from the approximate feature attributes of the first sub-dataset attaching a data identifier feature value to each data element of the first sub-dataset, so that a data element of the second sub-dataset can be traced back to a corresponding data element in the first sub-dataset;
outputting the second sub-dataset; and
storing the second sub-dataset in a second data storage layer.
Claim 2 further recites wherein the adjusted feature attributes are generated based on database normalization of the first sub-dataset.
Claim 3 further wherein the first data storage layer is an ingestion layer.
Claim 4 further recites wherein the second data storage layer is an integration layer.
Claim 5 further claims wherein the second sub-dataset is a normalized dataset.
Claim 6 further claim outputting the normalized dataset to a graphical user interface to display on a first user device associated with the first user in a third data storage layer.
Claim 7 further claims wherein the third data storage layer is a semantic layer.
Claim 8 further claims wherein the adjusted feature attributes are provided by user device associated with the first user.
Claim 9 further claims granting access to the second sub-dataset to a second user device; and
receiving, from the second user device, a second data request including at least one approximate feature attribute requested by the first user.
Claim 10 further claims generating, upon multiple requests of a same approximate features attribute by different users, a third sub-dataset including one or more data features common to the multiple requests.
Claim 11 further claims a first memory storing instructions;
a processor configured to execute the instructions to:
collect at least one user transactional behavior dataset, the user transactional behavior data including a plurality of user transactional behavior data elements, each user transactional behavior data element in the plurality of user transactional behavior data elements including one or more feature attributes;
generate a first sub-dataset in a first data storage layer of the multi-layered data storage system, the first sub-dataset including one or more feature attributes requested by a first user;
calculate one or more approximate feature attributes of the first sub-dataset, based on one or more adjusted feature attributes;
generate a second sub-dataset, wherein a data identifier feature value is attached to each data element of the second sub-dataset, so that each data element of the second sub-dataset can be traced back to a corresponding data element in the first sub-dataset; and
provide the second sub-dataset to a second user device associated with a second user in response to a request from the second user device, the request including the one or more approximate feature attributes;
a second memory, configured to host the first data storage layer, storing the first sub-dataset; and
a third memory, configured to host a second data storage layer, storing the second sub-dataset.
Claim 12 further claims a fourth memory, configured to host a third data storage layer, storing a third sub-dataset, the third sub-dataset including data features that have been previously requested by multiple users.
Claim 13 further claims wherein the adjusted feature attributes are generated based on database normalization of the first sub-dataset.
Claim 14 further recites wherein the first data storage layer is an ingestion layer.
Claim 15 further recites wherein the second data storage layer is an integration layer.
Claim 16 further claims wherein the second sub-dataset is a normalized dataset.
Claim 17 further claims wherein the second sub-dataset is a calculated dataset.
Claim 18 further claims instructions to output the normalized dataset to a graphical user interface to display on a first user device associated with the first user in a third data storage layer.
Claim 19 further recites wherein the third data storage layer is a semantic layer.
Claim 20 further recites wherein the adjusted feature attributes are provided by user device associated with the first user.
Regarding claim 1, applicant is to be noted that the steps or functions of "providing”, and “generating”, involve mental processes and/or generic computer functions. The functions of “calculating/calculate” are similar to a mathematical function. The function “storing" is considered as data gathering function. The function of “outputting” is an insignificant post solution activity.
Regarding claim 11, applicant is to be noted that the steps or functions of The function “collect" is considered as data gathering function. The functions of "provide”, and “generate”, involve mental processes and/or generic computer functions. The function of “calculate” is similar to a mathematical function. The function of “host” involves a mental process and/or generic computer function.
Step 2A, Prong One, claims 1, and 11 are found to include at least one judicial exception, that the resent claims recite steps that can be performed using the human mind, pen, and paper. According to the 2019 Revised Guidance, concepts performed in the human mind (including an observation, evaluation, judgement, or opinion) fall into the category of mental processes. See 2019 Revised Guidance, 84 Fed. Reg. at 52.
Step 2A, Prong Two of the eligibility analysis evaluates whether the claims as a whole integrate the recited judicial exception(s) into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.2019 PEG Section III(A)(2), 84 Fed. Reg. at 54-55. In particular, the claims recite the following bolded limitations understood to be additional limitations:
In addition to the abstract ideas recited in claims 1, and 11, the claimed method recites additional elements including a processor, a first data storage layer of the multi-layered data storage system, and a second data storage layer (claim 1), a multi-layered data storage system, a second user device, a second memory, and a third memory, a second data storage layer (claim 11). See Paragraphs [0045-0047] of applicant’s specification.
When considered in view of the claims as a whole, the recited computer elements do not integrate the abstract idea into a practical application because the computer elements are generic computer elements that are merely used as a tool to perform the recited abstract idea. As a result, claims 1, and 11 do not include additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
Performing steps or functions by a user device, processor or a computing system merely limits the abstraction to a computer field by execution by generic computers. See MPEP 2106.05.
As noted in MPEP 2106.04(d), limitations which amount to instructions to implement an abstract idea on a computer or merely using a computer as a tool, limitations which amount to insignificant extra-solution activity, and limitations which amount to generally linking to a particular technological environment do not integrate a practical exception into a practical application.
Consideration of the claimed steps of the claims as a combination do not change the analysis as they do not add anything compared to when the steps are considered separately. The claims recite a particular sequence of functions of processing and storing a consolidated, secured, standardized representation of transactional data that enables life-of-a-transaction analysis and the identification and delivery of actionable insights at the right-time.
Performance of these steps or functions technologically may present a meaningful limit to the scope of the claim does not reasonably integrate the abstraction into a practical application.
Step 2B: The elements discussed above with respect to the practical application in Step 2A, prong 2 are equally applicable to consideration of whether the claims amount to significantly more. Accordingly, the claims fail to recite additional elements which, when considered individually and in combination, amount to significantly more. Reconsideration of these elements identified as insignificant extra-solution activity as part of Step 2B does not change the analysis.
Providing, generating, calculating. Output and storing data by a processor or computer hardware amounts to receiving and processing data over a network has been recognized by the courts as well-understood, routine, and conventional (See MPEP 21065(d)(H), citing Symantec. 838 F.3d at ! 32 ! , 120 USPQ2d at l 362 (utilizing an intermediary computer to forward information): TU Communications LLC v. AV Auto. LLC, 823 F3d 607,610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission): OIP Techs., Inc., v, Amazon.com, Inc., 788 F3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir, 2015) (sending messages over a network: buy SAFE, Inc.v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
Positively reciting the processor does not change the analysis as these aspects are properly considered as additional elements which amount to instructions to apply with a computer.
These claimed elements also as found in the dependent claims are also recited at a high level of generality such that they amount to no more than mere instructions to apply the exception using a generic component.
In processing the claims, it is noted that the recitation of these additional elements do not impact the analysis of the claims because these elements in combination are noted only to be a general purpose computer or processor for performing basic or routine computer functions. These claimed elements are noted to a be a generic computer for accessing data similar to collecting data, storing data and performing routine and conventional functions.
The judicial exception is not integrated into a practical application. In particular, the claimed “controlling unit ” is recited at a high level of generality such they amount to no more than mere instructions to apply the exception using generic components. Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
As a result of the above analysis, claim 1, as well as claim 11, do not appear to be patent eligible under 101.
Accordingly, claims 1, and 11 are directed to an abstract idea.
Dependent claims 2-10 and 15-20 include additional elements beyond those recited by independent claims 1, and 11. The claimed steps do not amount to significantly more than the abstract idea, because they are well-understood, routine, and conventional computer functions in view of MPEP 2106 .05(d)(11). The recited computer elements do not amount to significantly more than the abstract idea because the computer elements are generic computer elements that are merely used as a tool to perform the recited abstract idea. As a result, claims 2-10 and 12-20 do not include additional elements that amount to significantly more than the abstract idea under Step 2B.
Therefore, the claims are directed to an abstract idea without additional elements amounting to significantly more than the abstract idea. Accordingly, claims 1-20 are rejected under 35 USC. 101 as being directed to non-statutory subject matter.
The prior art taken alone or in combination failed to teach or suggest:
“generating, using the processor, a second sub-dataset, wherein the second sub-dataset is formed from the approximate feature attributes of the first sub-dataset attaching a data identifier feature value to each data element of the first sub-dataset, so that a data element of the second sub-dataset can be traced back to a corresponding data element in the first sub-dataset; outputting the second sub-dataset; and storing the second sub-dataset in a second data storage layer” as recited in independent claim 1.
“generate a second sub-dataset, wherein a data identifier feature value is attached to each data element of the second sub-dataset, so that each data element of the second sub-dataset can be traced back to a corresponding data element in the first sub-dataset; and provide the second sub-dataset to a second user device associated with a second user in response to a request from the second user device, the request including the one or more approximate feature attributes; a second memory, configured to host the first data storage layer, storing the first sub-dataset; and a third memory, configured to host a second data storage layer, storing the second sub-dataset” as recited in independent claim 11.
- Schwartz et al (US Publication No. US 20070088667 A1) teaches a data processing method extracts first data and second data from an online transactional processing module by an online analytical processing module. The first data is descriptive of past account transactions and the second data is descriptive of at least one rule for identification of a sub-set of a set of accounts for which account specific data processing actions are required. The at least one rule is applied to the first data for identification of the sub-set of accounts and the respective account specific data processing actions. A database table is generated for identification of the sub-set of accounts and for specification of the respective account specific data processing actions. The database table is read by the online transactional processing module.
- Singhal et al (US Patent No. 12,032,721) teaches transactional data that refers to any data representing transactions associated with the plurality of users. The transactional data is transactional records (i.e. records of transactions) stored for the plurality of users. For example, the transactions may be financial transactions, such as credit card purchases, money transfers, etc.
- Hahn-Carlson (WO 2005124631 A2) teach a method and system for processing and management of transactions involving the processing of interactions involving goods and/or services.
Conclusion
3. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. As per attached PTO 892 form.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROMAIN JEANTY whose telephone number is (571)272-6732. The examiner can normally be reached M-F 9AM to 5:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O'Connor can be reached on 571 272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ROMAIN JEANTY/Primary Examiner, Art Unit 3624
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