Adding the Temporal Dimension to Search " A Case Study in Publication Search

The most well known search techniques are perhaps the PageRank and HITS algorithms. In this paper we argue that these algorithms miss an important dimension, the temporal dimension. Quality pages in the past may not be quality pages now or in the future. These techniques favor older pages because th...

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Veröffentlicht in:IEEE/WIC/ACM International Conference on web intelligence S. 543 - 549
Hauptverfasser: Yu, Philip S., Li, Xin, Liu, Bing
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: Washington, DC, USA IEEE Computer Society 19.09.2005
IEEE
Schriftenreihe:ACM Conferences
Schlagworte:
Applied computing > Document management and text processing > Document preparation > Multi > mixed media creation
Computer aided software engineering
Computer science
Drives
History
Human-centered computing > Human computer interaction (HCI) > Interaction paradigms > Hypertext > hypermedia
Information systems > Information retrieval
Information systems > Information retrieval > Document representation
Information systems > Information retrieval > Evaluation of retrieval results
Search engines
Web pages
Web search
ISBN:076952415X, 9780769524153
Online-Zugang:Volltext
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Zusammenfassung:The most well known search techniques are perhaps the PageRank and HITS algorithms. In this paper we argue that these algorithms miss an important dimension, the temporal dimension. Quality pages in the past may not be quality pages now or in the future. These techniques favor older pages because these pages have many in-links accumulated over time. New pages, which may be of high quality, have few or no in-links and are left behind. Research publication search has the same problem. If we use the PageRank or HITS algorithm, those older or classic papers will be ranked high due to the large number of citations that they received in the past. This paper studies the temporal dimension of search in the context of research publication. A number of methods are proposed to deal with the problem based on analyzing the behavior history and the source of each publication. These methods are evaluated empirically. Our results show that they are highly effective.
Bibliographie:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:076952415X
9780769524153
DOI:10.1109/WI.2005.21