Identifying frequent terms in text databases by association semantics

Existing information retrieval methods are mainly based on either term similarity or latent semantics. To reduce irrelevant information searched, this paper presents a new approach for information retrieval by applying the methodology of association rule mining to a text database. Association semantics among terms of a document and a query are considered, such that the semantic similarity between the document and query may be reduced if they are somewhat irrelevant.