TableRank: A ranking algorithm for table search and retrieval

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

7 Scopus citations

Abstract

Tables are ubiquitous in web pages and scientific documents. With the explosive development of the web, tables have become a valuable information repository. Therefore, effectively and efficiently searching tables becomes a challenge. Existing search engines do not provide satisfactory search results largely because the current ranking schemes are inadequate for table search and automatic table understanding and extraction are rather difficult in general. In this work, we design and evaluate a novel table ranking algorithm - TableRank to improve the performance of our table search engine TableSeer. Given a keyword based table query, TableRank facilities TableSeer to return the most relevant tables by tailoring the classic vector space model. TableRank adopts an innovative term weighting scheme by aggregating multiple weighting factors from three levels: term, table and document. The experimental results show that our table search engine outperforms existing search engines on table search. In addition, incorporating multiple weighting factors can significantly improve the ranking results.

Original languageEnglish (US)
Title of host publicationAAAI-07/IAAI-07 Proceedings
Subtitle of host publication22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
Pages317-322
Number of pages6
StatePublished - Nov 28 2007
EventAAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference - Vancouver, BC, Canada
Duration: Jul 22 2007Jul 26 2007

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume1

Other

OtherAAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
CountryCanada
CityVancouver, BC
Period7/22/077/26/07

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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    Liu, Y., Bai, K., Mitra, P., & Giles, C. L. (2007). TableRank: A ranking algorithm for table search and retrieval. In AAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference (pp. 317-322). (Proceedings of the National Conference on Artificial Intelligence; Vol. 1).