An efficient relevant evaluation model in information retrieval and its application

In this paper, we propose an algorithm named matrix space model to compute the similarity between document and query. After analyzing the computation model on similarity between document and query, we point out the disadvantages of Boolean model and vector space model. We map the Boolean query statement to a matrix, which makes it easy to convert a traditional Boolean logical query statement into a matrix so we can improve the retrieval performance because this model allows a document might be retrieved in a clear Boolean view even it matches the query partially. On the base of them, we implement an agent-based selective information retrieval.