Vector model improvement by FCA and Topic Evolution

Abstract. Presented research is based on standard methods of information retrieval using the vector model for representation of documents (objects). The vector model is often expanded to get better precision and recall. In this article we have mentioned two approaches of vector model expansion. The first approach is based on hierarchical clustering. Its goal is to find a list of all documents they have most similar topic to the requested document. The second one is the document classification based on formal concept analysis. We have tried to evaluate all concepts and computed the importances of documents. At last have compared the results of our approach based on formal concept analysis and the results of classical vector model