Popularity weighted ranking for academic digital libraries

Yang Sun, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Scopus citations

Abstract

We propose a popularity weighted ranking algorithm for academic digital libraries that uses the popularity factor of a publication venue overcoming the limitations of impact factors. We compare our method with the naive PageRank, citation counts and HITS algorithm, three popular measures currently used to rank papers beyond lexical similarity. The ranking results are evaluated by discounted cumulative gain(DCG) method using four human evaluators. We show that our proposed ranking algorithm improves the DCG performance by 8.5% on average compared to naive PageRank, 16.3% compared to citation count and 23.2% compared to HITS. The algorithm is also evaluated by click through data from CiteSeer usage log.

Original languageEnglish (US)
Title of host publicationAdvances in Information Retrieval - 29th European Conference on IR Research, ECIR 2007, Proceedings
PublisherSpringer Verlag
Pages605-612
Number of pages8
ISBN (Print)3540714944, 9783540714941
DOIs
StatePublished - 2007
Event29th European Conference on IR Research, ECIR 2007 - Rome, Italy
Duration: Apr 2 2007Apr 5 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4425 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other29th European Conference on IR Research, ECIR 2007
CountryItaly
CityRome
Period4/2/074/5/07

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Popularity weighted ranking for academic digital libraries'. Together they form a unique fingerprint.

  • Cite this

    Sun, Y., & Giles, C. L. (2007). Popularity weighted ranking for academic digital libraries. In Advances in Information Retrieval - 29th European Conference on IR Research, ECIR 2007, Proceedings (pp. 605-612). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4425 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-71496-5_57