The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Feb. 28, 2023
Filed:
Nov. 21, 2018
International Business Machines Corporation, Armonk, NY (US);
Mandar Mutalikdesai, Bengaluru, IN;
Arjun Das, Bengaluru, IN;
Ratnanu Ghosh-Roy, Buckinghamshire, GB;
Sudarsan Lakshminarayanan, Bengaluru, IN;
Veerababu Moodu, Bengaluru, IN;
Raunak Swarnkar, Gandhinagar, IN;
Anagha M, Bengaluru, IN;
Shrishti Aggarwal, Delhi, IN;
Lavina Durgani, Bengaluru, IN;
International Business Machines Corporation, Armonk, NY (US);
Abstract
Documents needing to be analyzed for various reasons, such as financial crimes, are ranked by examining the topicality and sentiment present in each document for a given subject of interest. In one approach a given document is classified to determine its category, and entity recognition is used to identify the subject of interest. Passages from the document that relate to the entity are grouped and analyzed for sentiment to generate a sentiment score. Documents are then ranked based on the sentiment scores. In another approach, a classification probability score is computed for each passage representing a likelihood that the passage relates to a category of interest, and the document is ranked based on the sentiment scores and the classification probability scores. The category classification uses an ensemble of natural language text classifiers. One of the classifiers is a naïve Bayes classifier with feature vectors generated using Word2Vec modeling.