A context sensitive document indexing approach for Information Retrieval

Information retrieval is used to retrieve the information according to the user query. In the existing model the information retrieval is done by analyzing the whole document to answer a query and the terms related to the query are extracted. The indexing weight is applied to all the terms and finally it provides the response to the user. In the existing model they did not take the context into consideration so the information cannot be retrieved efficiently. In this paper, we propose a context-sensitive document indexing approach for information retrieval. The content carrying terms and background terms are separated by using lexical association. Indexing weight is calculated for content carrying terms. The term having the highest indexing weight is considered as the most salient sentence and these sentences are extracted and the document summarization is done. Then according to the user query the information is retrieved, the query is considered as the keyword. Then this keyword is matched with the summarized document. Once the keyword is matched, the particular sentences were extracted by using indexing algorithm. Finally these sentences are provided as the responses for the user. By using this approach, the information retrieval can be done effectively.