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.
Courseault Trumbach, Cherie Journal of Information Science 2007
Abstract:
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.