PATENT CLAIM ANALYSIS

Application Number: 16055625
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2018-12
Patent Classification: ["704", "009000"]

Abstract:
Automatic semantic analysis for characterizing and correlating literary elements within a digital work of literature is accomplished by employing natural language processing and deep semantic analysis of text to create annotations for the literary elements found in a segment or in the entirety of the literature, a weight to each literary element and its associated annotations, wherein the weight indicates an importance or relevance of a literary element to at least the segment of the work of literature; correlating and matching the literary elements to each other to establish one or more interrelationships; and producing an overall weight for the correlated matches.

Claim (Index 19):
The computer system as set forth in  claim 17  wherein the encoded program instructions are further for:\n automatically breaking the digital work of literature into segments according to one or more rules selected from the group consisting of proportionally dividing the entire digital work of literature into a fixed number of segments and dividing the entire digital work of literature into segments according to fixed lengths of the segments; \n calculating a segment-bound overall weight for a literary element within the segment by applying a mathematical weighting function to the one or more attributes; and \n calculating an overall weight for a literary element within a plurality of segments by applying a mathematical weighting function to one or more segment-bound overall weights.

Metadata:
- Claim Count in Document: 47.0
- Percentile: 96.0
- Lexical Diversity: 1.84483
- Patent Class: 704.0
- Transitional Phrase Type: closed
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14489652', '14094889', '14094911', '14488424', '14094934']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3070435305807659
- 35 USC 102 Novelty (BERT): 0.5336892125447517
- Combined Prediction Score: 0.3297080987771645
- Mean Citation Score: 285.436186
- Max Citation Score: 357.97626
- Similarity Product: 241.8334811644829

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

Dataset: test