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Journal of Information Science
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Identifying synonymous concepts in preparation for technology mining

Cherie Courseault Trumbach

Department of Management, University of New Orleans, New Orleans, USA, ctrumbac{at}uno.edu

Dinah Payne

Department of Management, University of New Orleans, New Orleans, USA

In this research, the development of a `concept-clumping algorithm' designed to improve the clustering of technical concepts is demonstrated . The algorithm developed first identifies a list of technically relevant noun phrases from a cleaned extracted list and then applies a rule-based algorithm for identifying synonymous terms based on shared words in each term. An assessment of the algorithm found that the algorithm has an 89—91% precision rate, was successful in moving technically important terms higher in the term frequency list, and improved the technical specificity of term clusters.

Key Words: text mining • data quality • knowledge discovery • term similarity • text cleaning

This version was published on December 1, 2007

Journal of Information Science, Vol. 33, No. 6, 660-677 (2007)
DOI: 10.1177/0165551506076401
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[Abstract] [PDF]