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A temporally adaptive content-based relevance ranking algorithm

Perkiö, Jukka, Buntine, Wray, Tirri, Henry·2005·Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
DOI 10.1145/1076034.1076171
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Abstract

In information retrieval relevance ranking of the results is one of the most important single tasks there are. There are many diffierent ranking algorithms based on the content of the documents or on some external properties e.g. link structure of html documents.We present a temporally adaptive content-based relevance ranking algorithm that explicitly takes into account the temporal behavior of the underlying statistical properties of the documents in the form of a statistical topic model. more we state that our algorithm can be used on top of any ranking algorithm.

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Research works printed but not linked: 5

  1. 10.1145/383952.383954 · DOI
  2. 10.1145/1008992.1009048 · DOI
  3. W. Buntine and A. Jakulin . Applying discrete PCA in data analysis . In UAI-2004 Banff , 2004 . W. Buntine and A. Jakulin.Applying discrete PCA in data analysis. In UAI-2004 Banff, 2004.
  4. L. Page , S. Brin , R. Motwani , and T. Winograd . The pagerank citation ranking: Bringing order to the web. Technical report , Stanford Digital Library Technologies Project , 1998 . L. Page, S. Brin, R. Motwani, and T. Winograd. The pagerank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project, 1998.
  5. 10.5555/1025132.1026407 · DOI

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Metadata

Authors
Perkiö, J., Buntine, W., & Tirri, H.
Affiliations
  • Helsinki Institute for Information Technology, HUT, Finland
  • Nokia Research Center
Venue
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Publisher
ACM
Published
2005-08-15
Pages
647-648
DOI
10.1145/1076034.1076171
Cited by
12
References
0
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)

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