Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/2237
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dc.contributor.authorSérgio Nunesen
dc.contributor.authorCristina Ribeiroen
dc.contributor.authorGabriel Daviden
dc.date.accessioned2017-11-16T13:23:31Z-
dc.date.available2017-11-16T13:23:31Z-
dc.date.issued2011en
dc.identifier.urihttp://repositorio.inesctec.pt/handle/123456789/2237-
dc.identifier.urihttp://dx.doi.org/10.1002/asi.21597en
dc.description.abstractIn real-world information retrieval systems, the underlying document collection is rarely stable or definitive. This work is focused on the study of signals extracted from the content of documents at different points in time for the purpose of weighting individual terms in a document. The basic idea behind our proposals is that terms that have existed for a longer time in a document should have a greater weight. We propose 4 term weighting functions that use each document's history to estimate a current term score. To evaluate this thesis, we conduct 3 independent experiments using a collection of documents sampled from Wikipedia. In the first experiment, we use data from Wikipedia to judge each set of terms. In a second experiment, we use an external collection of tags from a popular social bookmarking service as a gold standard. In the third experiment, we crowdsource user judgments to collect feedback on term preference. Across all experiments results consistently support our [...]en
dc.languageengen
dc.relation212en
dc.relation215en
dc.relation5448en
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.titleTerm Weighting based on Document Revision Historyen
dc.typearticleen
dc.typePublicationen
Appears in Collections:CSIG - Indexed Articles in Journals

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