An Information Retrieval Model Based on Latent Semantic Indexing with Intelligent Preprocessing

The primary goal of an information retrieval system is to retrieve all the documents that are relevant to the user query. Disparities between the vocabulary of the system's authors and that of their users pose difficulties when information is processed without human intervention. Preprocessing the documents and user queries using intelligence techniques to remove the ambiguities in representation and indexing is the current area of research. In this paper, we present a novel intelligent method that has been appended to existing stemming and stopword removal processes. We designed an information retrieval system based on the proposed method using latent semantic indexing. The experimental results of the system using the proposed method exhibits the superiority over other systems based on traditional preprocessing methods.