Utilizing term proximity for blog post retrieval.
Term proximity is effective for many information retrieval (IR) research fields yet remains unexplored in blogosphere IR. The blogosphere is characterized by large amounts of noise, including incohesive, off-topic content and spam. Consequently, the classical bag-of-words unigram IR models are not r...
| Publicado en: | Journal of the American Society for Information Science & Technology Vol. 64; no. 11; pp. 2278 - 2299 |
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| Autores principales: | , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Nov2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104146117&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104146117 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15322882 IGD jtl: Journal of the American Society for Information Science & Technology issn: 15322882 maglogo: Y pubinfo: dt: Nov2013 vid: 64 iid: 11 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 104146117 91102965 10.1002/asi.22916 104146117 ppf: 2278 ppct: 21 formats: tig: atl: Utilizing term proximity for blog post retrieval. aug: au: Ye, Zheng He, Ben Wang, Lifeng Luo, Tiejian affil: School of Computer Science and Technology, Hangzhou Dianzi University sug: subj: Blogs Information Retrieval Methods Public Opinion Models, Statistical Information Science Methods Electronic Publishing Human Wilcoxon Rank Sum Test Funding Source ab: Term proximity is effective for many information retrieval (IR) research fields yet remains unexplored in blogosphere IR. The blogosphere is characterized by large amounts of noise, including incohesive, off-topic content and spam. Consequently, the classical bag-of-words unigram IR models are not reliable enough to provide robust and effective retrieval performance. In this article, we propose to boost the blog postretrieval performance by employing term proximity information. We investigate a variety of popular and state-of-the-art proximity-based statistical IR models, including a proximity-based counting model, the Markov random field (MRF) model, and the divergence from randomness (DFR) multinomial model. Extensive experimentation on the standard TREC Blog06 test dataset demonstrates that the introduction of term proximity information is indeed beneficial to retrieval from the blogosphere. Results also indicate the superiority of the unordered bi-gram model with the sequential-dependence phrases over other variants of the proximity-based models. Finally, inspired by the effectiveness of proximity models, we extend our study by exploring the proximity evidence between uery terms and opinionated terms. The consequent opinionated proximity model shows promising performance in the experiments. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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