PATENT CLAIM ANALYSIS

Application Number: 16366705
Application Type: Utility
Filing Date: 2019-03
Publication Date: 2019-07
Patent Classification: ["706", "025000"]

Abstract:
Deep learning is used to identify specific risks to an enterprise of a pending litigation and identify documents of interest for the litigation. The system involves mining and using existing classifications of data (e.g., from a litigation database) to train one or more deep learning algorithms, and then examining the electronically stored information with the trained algorithm, to generate a scored output that will enable enterprise personnel to review risks to the enterprise, e.g. to enable enterprise personnel to assess the nature and extent of the potential damage from the litigation, and to identify relevant documents that would be saved to prevent spoliation.

Claim (Index 7):
A method of using classified text and deep learning algorithms to identify risk and provide early warning comprising:\n creating one or more training datasets by mining one or more litigation databases for textual data corresponding to a specific threat or risk of interest; training one or more deep learning algorithms using said one or more training datasets; collecting and extracting a corpus of documents comprising electronically stored information stored by an enterprise; applying said one or more deep learning algorithms to said corpus of documents to identify and report one or more documents of interest in the said corpus of documents for an early assessment of the potential harm to the enterprise of said lawsuit; determining if said identified one or more documents of interest is a false positive or a true positive; and re-training said one or more deep learning algorithms if said identified one or more documents of interest is a false positive.

Metadata:
- Claim Count in Document: 23.0
- Percentile: 99.0
- Lexical Diversity: 1.66176
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15413323', '15406385', '15277458', '15414161', '15413335']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4508864864078372
- 35 USC 102 Novelty (BERT): 0.528287722909423
- Combined Prediction Score: 0.4586266100579957
- Mean Citation Score: 366.38186
- Max Citation Score: 372.55115
- Similarity Product: 332.3213399686873

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

Dataset: test