Term Weighting based on Document Revision History

dc.contributor.author Sérgio Nunes en
dc.contributor.author Cristina Ribeiro en
dc.contributor.author Gabriel David en
dc.date.accessioned 2017-11-16T13:23:31Z
dc.date.available 2017-11-16T13:23:31Z
dc.date.issued 2011 en
dc.description.abstract In 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.identifier.uri http://repositorio.inesctec.pt/handle/123456789/2237
dc.identifier.uri http://dx.doi.org/10.1002/asi.21597 en
dc.language eng en
dc.relation 212 en
dc.relation 215 en
dc.relation 5448 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Term Weighting based on Document Revision History en
dc.type article en
dc.type Publication en