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dc.contributor.authorIde, E.en_US
dc.contributor.authorSalton, Gerarden_US
dc.date.accessioned2007-04-09T21:02:57Z
dc.date.available2007-04-09T21:02:57Z
dc.date.issued1969-01en_US
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR69-29en_US
dc.identifier.urihttps://hdl.handle.net/1813/5887
dc.description.abstractA great deal of effort has been devoted in recent years to the evaluation of automatic or semi-automatic information retrieval systems. Recent evaluation results indicate that the search effectiveness presently achieved, or likely to be achievable in the foreseeable future, is much smaller than expected by a majority of the potential user population. Furthermore, theoretical advances in language analysis and data organization promise only relatively modest future improvements. The most significant advances in retrieval effectiveness are likely to be obtained by using adaptive techniques to extract information from the user population during the search process, leading to an improved organization of the data space and to more effective search and retrieval operations. Various user feddback techniques are described producing either modifications in the user queries i such a way as to bring these queries closer to existing groups of relevant documents, or modifications in the document space to bring relevant documents closer to the corresponding search requests. The feedback and space modification techniques are examined in detail, and the resulting efficiencies in the remote and retrieval operations are described. Descriptive Terms: Information retrieval, document retrieval, user feedback, relevance feedback, request modifications, document modifications, document grouping, clustering, adaptive search method, cluster searches, search effectiveness.en_US
dc.format.extent1376930 bytes
dc.format.extent730131 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleDynamic File Organization and Heuristic SearchStrategies in Information Retrievalen_US
dc.typetechnical reporten_US


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