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 10):
A computing device comprising:\n a memory containing machine readable medium comprising machine executable code having stored thereon instructions for performing a method of multi-modal electronic document classification; a processor coupled to the memory, the processor configured to execute the machine executable code to cause the processor to: receive, as input, an electronic document on which to train a machine learning classifier for the multi-modal electronic document classification; apply a first neural network to raw text extracted from the electronic document to determine a textual data representation; apply a second neural network to an image extracted from the electronic document to determine a visual data representation; calculate a correlation between the textual data representation and the visual data representation; generate a fusion representation based on the correlation, the textual data representation, and the visual data representation; and\n (iii) \n apply the machine learning classifier based on the fusion representation to classify a new electronic document.

Metadata:
- Claim Count in Document: 71.0
- Percentile: 99.0
- Lexical Diversity: 1.82692
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['16037194', '15656269', '14609869', '13605051', '16058476']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2743500104589688
- 35 USC 102 Novelty (BERT): 0.5413717244636694
- Combined Prediction Score: 0.3010521818594389
- Mean Citation Score: 224.403004
- Max Citation Score: 374.0646
- Similarity Product: 313.4171503368616

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