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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.

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Journal of Information Science


This is an author-produced, peer-reviewed version of this article. The final, definitive version of this document can be found online at Journal of Information Science, published by SAGE. Copyright restrictions may apply.