Added by Geoff Sauer on Sep 20, 2008.
Average rating: 4.33/5.00 (n=3, std dev: 1.15)
 


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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