In this research, the development of a `concept-clumping algorithm\u27 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
