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EVALUATING THE EFFECTIVENESS OF QUERY-DOCUMENT CLUSTERING USING THE QDSM MEASURE

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dc.creatorCLAUDIO ORLANDO GUTIÉRREZ SOTO
dc.date2020
dc.date.accessioned2025-01-10T15:18:05Z
dc.date.available2025-01-10T15:18:05Z
dc.date.issued2020
dc.description.abstractIT IS WELL DOCUMENTED THAT THE AVERAGE LENGTH OF THE QUERIES SUBMITTED TO WEB SEARCH ENGINES IS RATHER SHORT, WHICH NEGATIVELY IMPACTS THE ENGINES? PERFORMANCE, AS MEASURED BY THE PRECISION METRIC. IT IS ALSO WELL KNOWN THAT AMBIGUOUS KEYWORDS IN A QUERY MAKE IT HARD TO IDENTIFY WHAT EXACTLY SEARCH ENGINE USERS ARE LOOKING FOR. ONE WAY TO TACKLE THIS CHALLENGE IS TO CONSIDER THE CONTEXT IN WHICH THE QUERY IS SUBMITTED, MAKING USE OF QUERY-SENSITIVE SIMILARITY MEASURES (QSSM). IN THIS PAPER, A PARTICULAR QSSM KNOWN AS THE QUERY-DOCUMENT SIMILARITY MEASURE (QDSM) IS EVALUATED, QDSM IS DESIGNED TO DETERMINE THE SIMILARITY BETWEEN TWO QUERIES BASED ON THEIR TERMS AND THEIR RANKED LISTS OF RELEVANT DOCUMENTS. TO THIS EXTENT, F-MEASURE AND THE NEAREST NEIGHBOR (NN) HAVE BEEN EMPLOYED TO ASSESS THIS APPROACH OVER A COLLECTION OF AOL QUERY LOGS. FINAL RESULTS REVEAL THAT BOTH THE AVERAGE LINK ALGORITHM AND WARD?S METHOD PRESENT BETTER RESULTS USING QDSM THAN COSINE SIMILARITY.
dc.formatapplication/pdf
dc.identifier.doi10.25046/aj0506105
dc.identifier.issn2415-6698
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/11362
dc.languagespa
dc.publisherADVANCES IN SCIENCE, TECHNOLOGY AND ENGINEERING SYSTEMS JOURNAL
dc.relation.uri10.25046/aj0506105
dc.rightsPUBLICADA
dc.titleEVALUATING THE EFFECTIVENESS OF QUERY-DOCUMENT CLUSTERING USING THE QDSM MEASURE
dc.title.alternativeEVALUACIÓN DE LA EFICACIA DE LA AGRUPACIÓN EN CLÚSTERES DE DOCUMENTOS DE CONSULTA MEDIANTE LA MEDIDA QDSM
dc.typeARTÍCULO
dspace.entity.typePublication
ubb.EstadoPUBLICADA
ubb.Otra ReparticionDEPARTAMENTO DE SISTEMAS DE INFORMACION
ubb.SedeCONCEPCIÓN
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