PATENT CLAIM ANALYSIS

Application Number: 16271847
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2020-01
Patent Classification: ["382", "158000"]

Abstract:
A method comprising operating at least one hardware processor for: receiving, as input, a plurality of electronic documents, training a machine learning classifier based, at least on part, on a training set comprising: (i) labels associated with the electronic documents, (ii) raw text from each of said plurality of electronic documents, and (iii) a rasterized version of each of said plurality of electronic documents, and applying said machine learning classifier to classify one or more new electronic documents.

Claim (Index 3):
The method of  claim 1 , wherein the applying the first neural network further comprises:\n generating, by the computer, the textual data representation of said extracted text as a fixed length vector.

Metadata:
- Claim Count in Document: 71.0
- Percentile: 99.0
- Lexical Diversity: 1.82692
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16037194', '15656269', '14609869', '13605051', '16058476']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2991382089669022
- 35 USC 102 Novelty (BERT): 0.5435579459552021
- Combined Prediction Score: 0.3235801826657322
- Mean Citation Score: 224.403004
- Max Citation Score: 374.0646
- Similarity Product: 291.99552218077184

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