Publication | Closed Access
Full Text Searching and Information Overload
24
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References
1998
Year
EngineeringInformation Retrieval TestsQuery ModelSemanticsSemantic WebCorpus LinguisticsText MiningNatural Language ProcessingInformation RetrievalData ScienceComputational LinguisticsInformation Retrieval ApplicationsRelevance FeedbackQuery ExpansionFull Text SearchingLanguage StudiesMachine TranslationSearch TechnologyInformation SearchKnowledge RetrievalDocument BaseSearch Engine IndexingLinguisticsInteractive Information Retrieval
This article classifies information retrieval applications into three classes depending on the correspondence between a user's request and the queries posed to the document base. It is argued that the mapping of requests (on a semantic level) to formalized queries (often on a lexical level) determines the range of retrieval effectiveness that may be obtained and that this classification may explain the discrepancy found in some information retrieval tests. It may also shed new light on a debate in the profession about the efficiency of retrieval systems in relation to precision, recall and information overload.