PATENT CLAIM ANALYSIS

Application Number: 16059399
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2020-02
Patent Classification: ["null", "null"]

Abstract:
An example method described herein involves receiving a data input; identifying a plurality of topics in the data input; determining an underrepresented set of data for a first set of topics of the plurality of topics based on a plurality of knowledge graphs associated with the first set of topics; calculating a score for each topic of the first set of topics based on a representative learning technique; determining that the score for a first topic of the first set of topics satisfies a threshold score; selecting a topic specific knowledge graph based on the first topic; identifying representative objects that are similar to objects of the data input based on the topic specific knowledge graph; generating representation data that is similar to the data input based on the representative objects to balance the underrepresented set of data with a set of data associated with a second set of topics of the plurality of topics; and performing an action associated with the representation data.

Claim (Index 1):
A method, comprising:\n receiving, by a device, a data input; receiving, by the device, a domain knowledge graph associated with objects of the data input; identifying, by the device, a plurality of topics in the data input based on the domain knowledge graph; determining, by the device, a represented set of data for a first set of topics of the plurality of topics; determining, by the device, an underrepresented set of data for a second set of topics of the plurality of topics,\n the underrepresented set of data being determined using a representative learning technique, and \n the representative learning technique being machine learning; \n determining, by the device, a distance between an identified topic of the data input and a first topic in the domain knowledge graph; calculating, by the device, a score for the first topic based on relevance of each topic to the data input the distance; determining, by the device, that the score for the first topic satisfies a threshold score; determining, by the device and based on determining that the score for the first topic satisfies the threshold score, that the first topic of the plurality of topics is one topic of the second set of topics; selecting, by the device, a topic specific knowledge graph based on the first topic; identifying, by the device, objects of the data input based on the topic specific knowledge graph; identifying, by the device, representative objects that have a threshold level of similarity with the objects of the data input based on the topic specific knowledge graph; generating, by the device and based on the representative objects, representation data that is of a similar data type to the data input and increases an amount of data associated with the underrepresented set of data,\n generating the representation data comprising:\n substituting a representative object, of the representative objects, with an object, of the objects of the data input, based on an edge distance of the representative object from the object of the data input in the topic specific knowledge graph; and \n \n performing, by the device, an action associated with the representation data.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 96.0
- Lexical Diversity: 3.14545
- Patent Class: nan
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14928210', '15687114', '15404932', '15040972', '14793033']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.528488751618702
- 35 USC 102 Novelty (BERT): 0.5043339312421316
- Combined Prediction Score: 0.5260732695810449
- Mean Citation Score: 224.936594
- Max Citation Score: 234.10284
- Similarity Product: 142.2810658379459

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

Dataset: test