document: Navigationaided retrieval Users searching for information in hypermedia environments often perform querying followed by manual navigation . Yet , the conventional text\/hypertext retrieval paradigm does not explicity take post-query navigation into account . This paper proposes a new retrieval paradigm , called navigation-aided retrieval ( NAR ) , which treats both querying and navigation as first-class activities . In the NAR paradigm , querying is seen as a means to identify starting points for navigation , and navigation is guided based on information supplied in the query . NAR is a generalization of the conventional probabilistic information retrieval paradigm , which implicitly assumes no navigation takes place . This paper presents a formal model for navigation-aided retrieval , and reports empirical results that point to the real-world applicability of the model . The experiments were performed over a large Web corpus provided by TREC , using human judgments on a new rating scale developed for navigation-aided retrieval . In the case of ambiguous queries , the new retrieval model identifies good starting points for post-query navigation . For less ambiguous queries that need not be paired with navigation , the output closely matches that of a conventional retrieval system .
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