Information Retrieval Using Context Based Document Indexing and Term Graph

Abstract

Information retrieval is task of retrieving relevant information according to query of user. An idea is presented in this paper about document retrieval using context based indexing and term weighting approach. Here lexical association is used to separate content carrying terms and background terms. Content carrying terms are used as they give idea about theme of the document. Indexing weight calculation is done for content carrying terms. Lexical association measure is used to calculate indexing weight of terms. The term having higher indexing weight is considered as important and sentence which contains these terms is also important. The summary of document is prepared. The graph of word approach is used here for information retrieval. The terms are weighted according to in-degree of vertices in document graph. When user enters search query, the important terms are matched with the terms with higher weights in order to retrieve documents. The documents which are relevant are retrieved according to weight of terms. Weight of term is determined using term graph. Term weight – Inverse document frequency scoring function is used to retrieve relevant documents. Using this approach information can be retrieved efficiently. Performance of retrieval will be improved as time required to search documents is less using proposed approach.