document: Mining anchor text for query refinement When searching large hypertext document collections , it is often possible that there are too many results available for ambiguous queries . Query refinement is an interactive process of query modification that can be used to narrow down the scope of search results . We propose a new method for automatically generating refinements or related terms to queries by mining anchor text for a large hypertext document collection . We show that the usage of anchor text as a basis for query refinement produces high quality refinement suggestions that are significantly better in terms of perceived usefulness compared to refinements that are derived using the document content . Furthermore , our study suggests that anchor text refinements can also be used to augment traditional query refinement algorithms based on query logs , since they typically differ in coverage and produce different refinements . Our results are based on experiments on an anchor text collection of a large corporate intranet .
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