Please use this identifier to cite or link to this item: http://hdl.handle.net/10216/98147
Author(s): Sérgio Nunes
Cristina Ribeiro
Gabriel David
Title: Term Weighting Based on Document Revision History
Issue Date: 2011
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 thesis. We show that temporally aware measures, specifically the proposed revision term frequency and revision term frequency span, outperform a term-weighting measure based on raw term frequency alone.
Subject: Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
URI: http://hdl.handle.net/10216/98147
Document Type: Artigo em Revista Científica Internacional
Rights: restrictedAccess
Appears in Collections:FEUP - Artigo em Revista Científica Internacional

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