International Business Machines Corporation

Sudarsan Lakshminarayanan

Mandar Mutalikdesai

Anagha M

Lavina Durgani

Raunak Swarnkar

Arjun Das

Shrishti Aggarwal

Ratnanu Ghosh-Roy

Veerababu Moodu

Ashish Rao

Sandipto Neogi

Simardeep Singh Arneja

Arnika Kumar

Yash Vardhan Singh

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 na&#xef;ve Bayes classifier with feature vectors generated using Word2Vec modeling.

Contextual interestingness ranking of documents for due diligence in the banking industry with entity grouping

An approach for enhancing user communication with a chatbot is provided. In an embodiment, a communication from a user using a chatbot application is received. One or more intents related to the user communication are identified, with each intent having a respective confidence score. Further, any number of attributes related to the user communication are extracted. If multiple viable intents are found (e.g., intents having a confidence score exceeding a predefined threshold), then relationships between the extracted attributes are derived to establish a context. Based on the context, a disambiguation question is generated to clarify an actual intent of the user.

Enhanced conversational bots processing

Contextual interestingness ranking of documents for due diligence in the banking industry with topicality grouping

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Bengaluru, India

Sudarsan Lakshminarayanan