The research on similarity for measuring document relevance is an important field in information retrieval. Many researchers are using concept lattice defined in Formal Concept Analysis (FCA) as a basis for measuring query-document relevance in text retrieval, i.e. Concept lattice-based ranking (CLR). However, formal Concept Analysis's notion of similarity for measuring documents relevance in text retrieval is only based on the shortest path linking the query to the document. It is not well defined. To resolve the problems of this approach, first, we evaluate reasonable different weights of edges in the Hasse diagram based on the conceptual generality or specificity. Second, we present a user profile based on Concept Lattice, and the algorithm for constructing Concept Lattice based user profile is provided. Third, we present a combination CLR approach by measuring the similarity among query, user profile and document according to the relation between query and user interest based on Concept Lattice. Our experiment shows that documents retrieved by our combination CLR approach achieve a higher measure of precision than the traditional CLR approach.
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