A Fuzzy-Cluster based Semantic Information Retrieval System

Due to the increasing number of digital document repositories there is a heavy demand for information retrieval systems and therefore, information retrieval is still appearing as an emerging area of research. The information retrieval technology these days focuses on achieving better performance under different context by extracting documents most appropriate to the user’s query. Majority of the classical keyword based retrieval techniques does not focus on semantic meanings and therefore, are found to be less effective in reconstructing the actual information conveyed in the context. Also, retrieval of the relevant documents depends on appropriate analysis of the query terms. As words are polysemic, their actual meanings are influenced by their relationships with other words and their syntactic roles in the sentence. This work presents a fuzzy-cluster based semantic information retrieval model that considers these relationships to determine the exact meaning of the user query and extracts relevant documents as per their relevance scores.