Fuzzy Latent Semantic Query Expansion Model for Enhancing Information Retrieval

One natural and successful technique to have retrieved documents that is relevant to users’ intention is by expanding the original query with other words that best capture the goal of users. However, no matter the means implored on the clustered document while expanding the user queries, only a concept driven document clustering technique has better capacity to spawn results with conceptual relevance to the users’ goal. Therefore, this research extends the Concept Based Thesaurus Network document clustering techniques by using the Latent Semantic Analysis tool to identify the Best Fit Concept Based Document Cluster in the network. The Fuzzy Latent Semantic Query Expansion Model process achieved a better precision and recall rate values on experimentation and evaluations when compared with some existing information retrieval approaches.