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 communication is responsive to application filed on 08/02/2023.
Claims 1-20 are presented for 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 an abstract idea without significantly more.
Step 1 (Does this claim fall within at least one statutory category?):
Claims 1-8 are directed to a system.
Claims 9-16 are directed to a system.
Claims 17-20 are directed to a product.
Therefore, claims 1-20 fall into at least one of the four statutory categories.
Step 2A, Prong 1: ((a) identify the specific limitation(s) in the claim that recites an abstract idea: and (b) determine whether the identified limitation(s) falls within at least one of the groups of abstract ideas enumerates in MPEP 2106.04(a)(2)):
Claim 1:
A system comprising:
at least one processor [e.g. a generic computer element for performing a generic computer function]; and
a storage to store instructions that, when executed by the at least one processor [e.g. a generic computer element for performing a generic computer function], cause the at least one processor to perform operations comprising:
analyze a data model to identify a first set of attributes present within the data model [“mental process i.e. concepts performed in the human mind or with pen and paper (including an observation, evaluation judgement, opinion)];
based on the first set, identify a data model standard with which the data model is to comply, wherein the standard requires a second set of attributes to be present in complying data models [“mental process i.e. concepts performed in the human mind or with pen and paper (including an observation, evaluation judgement, opinion)];
compare the first and second sets to identify a third set of attributes required by the standard, but not present in the data model [“mental process i.e. concepts performed or with pen and paper (including an observation, evaluation judgement, opinion)];
based on weightings of priority of the attributes of the third set, identify at least one highest priority change to apply to the data model to increase compliance of the data model with the standard [“mental process i.e. concepts performed in the human mind or with pen and paper (including an observation, evaluation judgement, opinion)];
present a user interface (UI) requesting approval to apply the at least one highest priority change to the data model [e.g. a generic computer element for performing a generic computer function]; and
apply the at least one highest priority change to the data model and update at least one of the weightings of priority of the attributes of the third set based on whether approval to apply the at least one highest priority change is received via the UI [“mental process i.e. concepts performed in the human mind or with pen and paper (including an observation, evaluation judgement, opinion)].
Step 2A, Prong 2 (1. Identifying whether there are any additional elements recited in the claim beyond the judicial exception; and 2. Evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application): The claim is directed to the judicial exception.
Claim 1 recites additional elements of “processor”, “storage” and “present”. The additional elements of “processor”, “storage” and “present” recited at a high level of generality (e.g. a generic computer element for performing a generic computer functions) such that it amounts to no more than mere application of the judicial exception using generic computer component(s). Accordingly, the additional element(s) of each of this claim does not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step 2B: (Does the claim recite additional elements that amount to significantly more than the judicial exception? No): As discussed above with respect to the integration of the abstract into a practical application, the additional elements of “processor”, “storage” and “present” amount to no more than mere instructions to apply the judicial exception using generic computer component(s). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
As per claims 2-8, the claims fall into [“mental process i.e. concepts performed in the human mind or with pen and paper (including an observation, evaluation judgement, opinion)].
As per Claims 9-20, claims 9-20 recite limitations analogous in scope to those of claims 1-8, and as such are similarly rejected.
Allowable Subject Matter
Claims 1-20 are allowable over prior arts.
The following is a statement of reasons for the indication of allowable subject matter:
Rashidi et al (A. J. Rashidi, A. Rezakhani, “A New approach to ranking attributes in attribute based access control using decision fusion”, pgs. 803-812, 2017) discloses creates the quantitative capability which we named it quantitative ABAC and is based on decision fusion, determine the attributes which have the most important role in the enterprises access management. Then, the experts consider and prioritize the attributes to determine which of attributes are more important than others, provide the weights as the importance of access control attributes based on decision-makers’ viewpoints by utilizing ordered weighted averaging for the proposed prioritization (Abstract); create a novel method that grant the access regard in ranking the access attributes (pg. 804 left side column); establish a general framework that use decision-maker information in decision fusion and create appropriate rankings between access control attributes until the importance rate of each of parameters involved indecision-making is detected well (pg. 806 left side column).
AGRAWAL et al (US Publication No. 2009/0024551 A1) discloses Provided are a method, system, and article of manufacture for managing validation models and rules to apply to data sets. A schema definition describing a structure of at least one column in a first data set having a plurality of columns and records providing data for each of the columns is received. At least one model is generated, wherein each model asserts conditions for at least one column in a record of the first data set. The schema definition and the at least one model are stored in a data quality model. Selection is received of a second data set and the data quality model. A determination is made as to whether a structure of the second data set is compatible with the schema definition in the selected data quality model. Each model in the data quality model is applied to the records in the second data set to validate the records in the second data set in response to determining that the structure of the second data set and the schema definition are compatible (Abstract); [0009] each generated model is applied to each record in the first data set to validate each record based on a result of applying each generated model to the columns of the record to generate benchmark statistics for the data quality model. The benchmark statistics are stored with the data quality model. Statistics on the records of the second data set are generated in response to applying each model in the data quality model to the records in the second data set. The generated statistics for the second data set are compared with the benchmark statistics to compare differences in data quality between the second data set and the first data set; [0015] In a further embodiment, the schema definition specifies a data type and column name for selected columns in the first data set. Data in at least one column in the second data set that is not compatible with one column format specified in the schema definition is transformed to a format compatible with the structure of the schema definition in response to determining that the structure of the second data set is incompatible with the schema definition in the selected data quality model, wherein the models are applied to the transformed data in the second data set.
However, none of the cited prior art references of record fully anticipate or render obvious the independent claims in particular the limitations of:
“compare the first and second sets to identify a third set of attributes required by the standard, but not present in the data model; based on weightings of priority of the attributes of the third set, identify at least one highest priority change to apply to the data model to increase compliance of the data model with the standard; present a user interface (UI) requesting approval to apply the at least one highest priority change to the data model; and apply the at least one highest priority change to the data model and update at least one of the weightings of priority of the attributes of the third set based on whether approval to apply the at least one highest priority change is received via the UI” as recited in claim 1,
“compare the first and second sets to identify a third set of attributes required by the standard, but not present in the data model; based on weightings of priority of the attributes of the third set, identify at least one highest priority change to apply to the data model to increase compliance of the data model with the standard; visually present, on a display of a remote device, a request for approval to apply the at least one highest priority change to the data model; and apply the at least one highest priority change to the data model and update at least one of the weightings of priority of the attributes of the third set based on whether approval to apply the at least one highest priority change is received from the remote device” as recited in claim 9, and
“comparing the first and second sets to identify a third set of attributes required by the standard, but not present in the data model; based on weightings of priority of the attributes of the third set, identifying at least one highest priority change to apply to the data model to increase compliance of the data model with the standard; visually presenting, on a display of a remote device, a user interface (UI) requesting approval to apply the at least one highest priority change to the data model; receiving, at a processor, and from the remote device, a response to the request; and applying the at least one highest priority change to the data model and updating at least one of the weightings of priority of the attributes of the third set based on whether the response comprises approval to apply the at least one highest priority change” as recited in claim 17.
Conclusion
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KIBROM K. GEBRESILASSIE
Primary Examiner
Art Unit 2189
/KIBROM K GEBRESILASSIE/Primary Examiner, Art Unit 2189 07/18/2026
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