iRANK: An interactive ranking framework and its application in query-focused summarization

Furu Wei, Wenjie Li, Wei Wang, Yanxiang He

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

We address the problem of unsupervised ensemble ranking in this paper. Traditional approaches either combine multiple ranking criteria into a unified representation to obtain an overall ranking score or to utilize certain rank fusion or aggregation techniques to combine the ranking results. Beyond the aforementioned combine-then-rank and rank-then-combine approaches, we propose a novel rank-learn-combine ranking framework, called Interactive Ranking (iRANK), which allows two base rankers to "teach" each other before combination during the ranking process by providing their own ranking results as feedback to the others so as to boost the ranking performance. This mutual ranking refinement process continues until the two base rankers cannot learn from each other any more. The overall performance is improved by the enhancement of the base rankers through the mutual learning mechanism. We apply this framework to the sentence ranking problem in query-focused summarization and evaluate its effectiveness on the DUC 2005 data set. The results are encouraging with consistent and promising improvements.
Original languageEnglish
Title of host publicationACM 18th International Conference on Information and Knowledge Management, CIKM 2009
Pages1557-1560
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2009
EventACM 18th International Conference on Information and Knowledge Management, CIKM 2009 - Hong Kong, Hong Kong
Duration: 2 Nov 20096 Nov 2009

Conference

ConferenceACM 18th International Conference on Information and Knowledge Management, CIKM 2009
Country/TerritoryHong Kong
CityHong Kong
Period2/11/096/11/09

Keywords

  • Interactive ranking
  • Query-focused summarization
  • Rank-learn-combine
  • Sentence ranking
  • Unsupervised ensemble ranking

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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