Abstract:
The heart of an information retrieval system is its retrieval model. The model is used to capture the meaning of documents and queries, and determine from that the relevance of documents with respect to queries. As large sets of documents are now increasingly common, there is a growing need for fast and efficient information retrieval algorithms. The algorithms are embedded in the vector space model. The simple vector space model is based on literal matching of terms in the documents and the queries. This paper implements digital library information retrieval system. In this paper, when user's query is input to the system, system computes terms-document matrix of weight for information retrieval. Then the similarity is computed between query and all documents and the retrieved documents are ranked using similarity measure methods. Finally the system analyzes with precision and recall of information retrieval results.
