CoChat
Sign Up
Cited by 36

The DOI matches its Crossref record.

Freshness matters: in flowers, food, and web authority

Dai, Na, Davison, Brian D.·2010·Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
DOI 10.1145/1835449.1835471
Open this paper in CoChat — free account

Abstract

The collective contributions of billions of users across the globe each day result in an ever-changing web. In verticals like news and real-time search, recency is an obvious significant factor for ranking. However, traditional link-based web ranking algorithms typically run on a single web snapshot without concern for user activities associated with the dynamics of web pages and links. Therefore, a stale page popular many years ago may still achieve a high authority score due to its accumulated in-links. To remedy this situation, we propose a temporal web link-based ranking scheme, which incorporates features from historical author activities. We quantify web page freshness over time from page and in-link activity, and design a web surfer model that incorporates web freshness, based on a temporal web graph composed of multiple web snapshots at different time points. It includes authority propagation among snapshots, enabling link structures at distinct time points to influence each other when estimating web page authority. Experiments on a real-world archival web corpus show our approach improves upon PageRank in both relevance and freshness of the search results.

Overview

Integrity signals

Registry

Crossref · 10.1145/1835449.1835471

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 33

  1. A. Acharya , M. Cutts , J. Dean , P. Haahr , M. Henzinger , U. Hoelzle , S. Lawrence , K. Pfleger , O. Sercinoglu , and S. Tong . Information retrieval based on historical data . US Patent 7 , 346 ,839, USPTO, Mar. 2008 . A. Acharya, M. Cutts, J. Dean, P. Haahr, M. Henzinger, U. Hoelzle, S. Lawrence, K. Pfleger, O. Sercinoglu, and S. Tong. Information retrieval based on historical data. US Patent 7,346,839, USPTO, Mar. 2008.
  2. 10.1145/1498759.1498837 · DOI
  3. 10.1002/asi.20082 · DOI
  4. 10.1145/988672.988716 · DOI
  5. 10.1145/1135777.1135953 · DOI
  6. 10.1145/1242572.1242737 · DOI
  7. 10.1080/15427951.2005.10129110 · DOI · Paper page
  8. 10.1145/1526709.1526717 · DOI
  9. 10.5555/297805.297827 · DOI
  10. 10.1145/1008992.1009068 · DOI
  11. 10.1145/1132952.1132954 · DOI
  12. 10.1145/1066157.1066220 · DOI · Paper page
  13. 10.1145/1531914.1531917 · DOI
  14. 10.1145/312624.312664 · DOI
  15. 10.1145/1718487.1718489 · DOI · Paper page
  16. 10.1145/1645953.1646243 · DOI
  17. Google Inc. Google trends home page , 2010 . http://www.google.com/trends. Google Inc. Google trends home page, 2010. http://www.google.com/trends.
  18. T. Haveliwala , S. Kamvar , A. Kamvar , and G. Jeh . An analytical comparison of approaches to personalizing pagerank. Technical report , Stanford University , 2003 . T. Haveliwala, S. Kamvar, A. Kamvar, and G. Jeh. An analytical comparison of approaches to personalizing pagerank. Technical report, Stanford University, 2003.
  19. Internet Archive . The Internet Archive . 2010 . http://www.archive.org/. Internet Archive. The Internet Archive. 2010. http://www.archive.org/.
  20. 10.1145/345508.345545 · DOI
  21. K. Kise M. Junker A. Dengel and K. Matsumoto . Passage Retrieval Based on Density Distributions of Terms and Its Applications to Document Retrieval and Question Answering. In volume 2956 of LNCS pages 306 -- 327 . Springer Berlin/ Heidelberg 2004 . K. Kise M. Junker A. Dengel and K. Matsumoto. Passage Retrieval Based on Density Distributions of Terms and Its Applications to Document Retrieval and Question Answering. In volume 2956 of LNCS pages 306--327. Springer Berlin/Heidelberg 2004. · DOI
  22. J. M. Kleinberg . Authoritative sources in a hyperlinked environment . In Proc. of the ACM-SIAM Symposium on Discrete Algorithms (SODA-98) , pages 668 -- 677 , San Francisco, CA , Jan. 1998 . J. M. Kleinberg. Authoritative sources in a hyperlinked environment. In Proc. of the ACM-SIAM Symposium on Discrete Algorithms (SODA-98), pages 668--677, San Francisco, CA, Jan. 1998.
  23. 10.1109/WAIM.2008.100 · DOI
  24. 10.1145/1390334.1390412 · DOI
  25. 10.1145/1571941.1571994 · DOI
  26. NIST. Text REtrieval Conference (TREC) home page , 2010 . http://trec.nist.gov/. NIST. Text REtrieval Conference (TREC) home page, 2010. http://trec.nist.gov/.
  27. 10.1145/1321440.1321542 · DOI
  28. 10.1108/EUM0000000007186 · DOI
  29. S. M. Ross . Introduction to Probability Models , Ninth Edition . Academic Press, Inc. , Orlando, FL, USA , 2006 . S. M. Ross. Introduction to Probability Models, Ninth Edition. Academic Press, Inc., Orlando, FL, USA, 2006.
  30. 10.1109/ICDM.2006.51 · DOI
  31. B. Wu , V. Goel and B. D. Davison . Propagating Trust and Distrust to Demote Web Spam . In Proc. of WWW2006 MTW Workshop , 2006 . B. Wu, V. Goel and B. D. Davison. Propagating Trust and Distrust to Demote Web Spam. In Proc. of WWW2006 MTW Workshop, 2006.
  32. 10.1145/1321440.1321598 · DOI
  33. 10.1145/1013367.1013519 · DOI

Cited by

Sorted by citations

See all 36

Metadata

Authors
Dai, N., & Davison, B. D.
Affiliations
Lehigh University, Bethlehem, PA, USA
Venue
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Publisher
ACM
Published
2010-07-19
Pages
114-121
DOI
10.1145/1835449.1835471
Cited by
36
References
0
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review