Abstract: An associative search methodology is presented whereby words, phrases, entire documents or technical jargon are input to the system for the purposes of searching a database for like items. A self-organizing associative data structure utilizing Latent Semantic Analysis (LSA) combined with a Hierarchical Mixture of Experts (HME) neural network learning system tracks relationships between words and word groupings as well as user significance feedback to automatically expand the search so that data elements can be found which cross technological/taxonomic boundaries. This results in an increase in both recall and precision parameters for each individual user's search.