PATENT CLAIM ANALYSIS

Application Number: 16238619
Application Type: Utility
Filing Date: 2019-01
Publication Date: 2019-05
Patent Classification: ["705", "007290"]

Abstract:
A processor uses natural language processing to ingest product reviews for a plurality of products. Each of the products embodies a specific form for each of the plurality of product features. The processor analyzes the ingested product reviews for sentiments associated with the specific forms. The processor generates a sentiment score for each product feature based on the analysis. The processor ranks the plurality of product features based on the sentiment scores.

Claim (Index 3):
The method of  claim 1 , wherein the ingesting, by the processor using natural language processing, the product reviews comprises:\n converting, by a tokenizer running on the processor, sequences of characters within the product reviews into sequences of tokens by identifying word boundaries in the product reviews; determining, by a part-of-speech tagger running on the processor, a part of speech for each token and marking each token with its part of speech; identifying, by syntactic relationship identifier running on the processor, syntactic relationships amongst the tokens; and generating, by the processor and based on the identified syntactic relationships, parse trees for the product reviews.

Metadata:
- Claim Count in Document: 16.0
- Percentile: 99.0
- Lexical Diversity: 1.97436
- Patent Class: 705.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14930693', '14948853', '11951155', '12020483', '14339213']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1115608240728443
- 35 USC 102 Novelty (BERT): 0.5196162941463307
- Combined Prediction Score: 0.152366371080193
- Mean Citation Score: 192.001926
- Max Citation Score: 333.88428
- Similarity Product: 284.8541330972672

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

Dataset: test