International Business Machines Corporation

Abhishek Shrivastava

Amit P Bohra

Anand B Bhagwat

Swapnasarit Sahu

Manojkumar Pal

Naveen G Balani

A set of first results from a first query are received. Using a natural language processing technique, a set of second results using a second query having at least a portion of the first query and at least a portion of set of first results are generated, wherein the natural language processing technique comprises a machine learning model configured to analyze the set of first results. The set of second results are scored based upon a semantic comparison of the set of first results, the second query, and the set of second results. Using the scored set of the second results, a set of processed results are generated.

Managing a search

A method and system for managing a search is disclosed. The method and system can include receiving a set of first results from a first query. A set of categories can be identified based on the set of first results. The method and system can include generating a set of second results using a second query having at least a portion of the first query, at least a portion of the first results, and at least a portion of the set of categories. The method and system can also include scoring the set of second results based upon a relationship of the first query, the second query, and the set of second results.

A computer processor determines a first span of a communication, wherein a span includes content associated with one or more dialog statements. If the content of the first span contains one or more topic change indicators which are identified by at least one detector of a learning model, the computer processor, in response, generates scores for each of the one or more indicators. The computer processor aggregates scores of the one or more indicators of the first span, which may be weighted, to produce an aggregate score. The computer processor compares the aggregate score to a threshold value, wherein the threshold value is determined during training of the learning model, and the computer processor, in response to the aggregate score crossing the threshold value, determines a topic change has occurred within the first span.

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Pune, India

Abhishek Shrivastava