International Business Machines Corporation

Stanislav Georgiev

Yan Luo

Tala El Hallak

Gary Mazo

Peter Haumer

William John Scheid, Iii

Hongxia Li

Monvorath Phongpaibul

Rahamim Katan

Techniques for context-based keyword grouping for business rule mining are described herein. An aspect includes determining, based on a first corpus, a first list of keywords. Another aspect includes constructing a co-occurrence matrix based on the first list of keywords. Another aspect includes applying a clustering algorithm to the co-occurrence matrix to determine a first plurality of keyword groups. Another aspect includes presenting the first plurality of keyword groups to a user via a user interface.

Context-based keyword grouping

Aspects include a method for generating an initial ranking of a plurality of discovered keywords, in which the initial ranking is based on confidence levels. The method includes presenting the initial ranking to a user as a list that includes the plurality of discovered keywords. The method includes, in response to receiving a text string as a first input from the user, filtering the list of discovered keywords to generate a refined list of discovered keywords. The filtering includes searching the list of discovered keywords to rank keywords that match the input string using a fuzzy search. The method includes mapping a discovered keyword of the refined list to a business term using a fuzzy search. The method includes updating the initial ranking based on the mapping of the discovered keyword.

Discovering and displaying business artifact and term relationships

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Thornhill, Canada

Stanislav Georgiev