PATENT CLAIM ANALYSIS

Application Number: 16269514
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-08
Patent Classification: ["726", "023000"]

Abstract:
A set of resource requests that each includes authorization-supporting data for receiving a requested resource can be received. For each request, augmenting data associated with part of the data is retrieved, and it is determined whether access is authorized based on the augmenting data and the authorization-supporting data. A machine-learning model is trained using representations of the set of resource requests and the authorization determinations. Additional requests are processed by the trained model to generate corresponding authorization outputs. One or more identifiers to flag for inhibition of resource access are determined based on the authorization outputs. Upon detecting that a new resource request to access a particular resource includes an identifier of the one or more identifiers, a new authorization output is generated to inhibit access to the particular resource.

Claim (Index 1):
A system comprising:\n one or more data processors; and a non-transitory computer readable storage medium containing instructions which, when executed on the one or more data processors, cause the one or more data processors to perform actions including:\n detecting receipt of each of a set of resource requests, wherein each resource request of the set of resource requests was received from a user device and includes:\n an identification of a requested resource; and \n authorization-supporting data for receiving the requested resource, \n \n wherein the authorization-supporting data includes one or more characterizing parameters that characterize one or more events;\n for each resource request of the set of resource requests:\n retrieving, from a data source or data structure that is separate from the user devices from which the set of resource requests were received, augmenting data associated with a characterizing parameter of the one or more characterizing parameters included in the resource request; and \n generating a representation of the resource request that includes a set of key-value pairs, wherein each of at least some of the set of key-value pairs includes a value extracted from or derived from the resource request; \n \n training a machine-learning model using the representations of the set of resource requests and augmenting-based data that includes or is derived from the augmenting data, wherein the trained machine-learning model includes a dependency between one or more first keys identified in the set of key-value pairs and an output; \n processing, for each other resource request in another set of resource requests, another representation of the other resource request using the trained machine-learning model to generate an authorization output; \n identifying, based on a population analysis of the authorization outputs, one or more identifiers to flag for inhibition of resource access, wherein the one or more identifiers do not correspond to the one or more first keys; \n detecting that a new resource request includes an identifier of the one or more identifiers, wherein the new resource request identifies a particular resource and corresponds to a particular entity; and \n generating a new authorization output for the new resource request, \n wherein release of the new authorization output results in inhibiting the particular entity from access the particular resource.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 99.0
- Lexical Diversity: 2.07463
- Patent Class: 726.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15983475', '12790358', '14934063', '14747062', '14752530']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2591883103037988
- 35 USC 102 Novelty (BERT): 0.4503248816914277
- Combined Prediction Score: 0.2783019674425617
- Mean Citation Score: 150.39597199999997
- Max Citation Score: 155.81837
- Similarity Product: 131.1950658169061

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test