PATENT CLAIM ANALYSIS

Application Number: 16125251
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-01
Patent Classification: ["707", "737000"]

Abstract:
An exemplary method may comprise receiving a matrix for a set of documents, each cell of the matrix including a frequency value indicating a number of instances of a corresponding text segment in a corresponding document, receiving an indication of a relationship between two text segments, each of the two text segments associated with a first column and a second column, respectively, of the matrix, adjusting, for each document, a frequency value of the second column based on the frequency value of the first column, projecting each frequency value into a reference space to generate a set of projection values, identifying a plurality of subsets of the reference space, clustering, for each subset of the plurality of subsets, at least some documents that correspond to projection values, and generating a graph of nodes, each of the nodes identifying one or more of the documents corresponding to each cluster.

Claim (Index 1):
A non-transitory computer readable medium comprising instructions, the instructions being executable by a processing device processor to perform a method, the method comprising:\n receiving a set of document identifiers, a plurality of text segments, and a plurality of frequency values, each document identifier of the set of document identifiers identifying one of a plurality of documents, each of the plurality of text segments being associated with a particular document identifier of the set of document identifiers, each of the plurality of text segments being in at least one document of the plurality of documents which is identified by the particular document identifier, and each of the plurality of frequency values indicating a number of instances of a corresponding text segment in a corresponding document of the plurality of documents; receiving an indication of a relationship between a first text segment of the plurality of text segments and a second text segment of the plurality of text segments, the first text segment being associated with a first frequency value of the plurality of frequency values, the second text segment being associated with a second frequency value of the plurality of frequency values; adjusting, for each document, the second frequency value based on a frequency value of the first frequency value; projecting each frequency value of the plurality of frequency values into a reference space to generate a set of projection values in the reference space; identifying a plurality of subsets of the reference space, at least some of the plurality of subsets including at least some of the projection values of the set of projection values in the reference space; clustering, for each subset of the plurality of subsets, at least some documents of the set of documents that correspond to a subset of the set of projection values to generate clusters of one or more documents; and generating a graph of nodes, each of the nodes identifying one or more of the documents corresponding to each cluster.

Metadata:
- Claim Count in Document: 68.0
- Percentile: 97.0
- Lexical Diversity: 2.37681
- Patent Class: 707.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14533058', '15806265', '15896030', '14481546', '14639954']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1770752828054904
- 35 USC 102 Novelty (BERT): 0.5494616624706714
- Combined Prediction Score: 0.2143139207720085
- Mean Citation Score: 241.85292400000003
- Max Citation Score: 406.13974
- Similarity Product: 346.5079274516928

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

Dataset: test