International Business Machines Corporation

Thomas North Adams

Rachel Tzoref-Brill

Maria Rose Ward

Meghna Paruthi

Lucas Liu

Brian Midei

Dagmawi Sraj

Tianqiong Wang

Sarah W Huber

A computer-implemented method, and a computer system are provided for implementing dynamic and automatic altering a user profile based on machine learning and cognitive analysis to improve user performance. The user profile is dynamically altered based upon live data from multiple external data sources using machine learning and cognitive application programming interfaces (APIs) without explicit input from the user. The altered user profile is automatically stored for the user. The stored user profile is deployed for multiple selected user applications enabling enhanced performance for the user.

Implementing dynamically and automatically altering user profile for enhanced performance

An approach for determining similar text documents. The approach can calculate a first set of vectors for a first cluster of text documents and a first comparison vector for a text document of interest. The approach can select a subset of text documents from the cluster of text documents based on comparing the vectors from the first set of vectors to the first comparison vector and picking a predetermined number of closest comparison text documents. The approach can calculate a second set of vectors for the subset of documents and second comparison vector for the document of interest. The approach can generate similarity ratings for the subset of documents based on pairwise comparisons of the second comparison vector and the second set of vectors. The approach can generate a ranked list of the second cluster of text documents based on the similarity ratings.

Hybrid clustering and pairwise comparison document matching

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Round Rock, TX, United States of America

Thomas North Adams