Rhetorical relations for information retrieval

Christina Lioma*, Birger Larsen, Wei Lu

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

12 Citations (Scopus)

Abstract

Typically, every part in most coherent text has some plausible reason for its presence, some function that it performs to the overall semantics of the text. Rhetorical relations, e.g. contrast, cause, explanation, describe how the parts of a text are linked to each other. Knowledge about this so-called discourse structure has been applied successfully to several natural language processing tasks. This work studies the use of rhetorical relations for Information Retrieval (IR): Is there a correlation between certain rhetorical relations and retrieval performance? Can knowledge about a document's rhetorical relations be useful to IR? We present a language model modification that considers rhetorical relations when estimating the relevance of a document to a query. Empirical evaluation of different versions of our model on TREC settings shows that certain rhetorical relations can benefit retrieval effectiveness notably (>10% in mean average precision over a state-of-the-art baseline).

Original languageEnglish
Title of host publicationSIGIR'12 - Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval
Number of pages10
Publication date28 Sept 2012
Pages931-940
ISBN (Print)9781450316583
DOIs
Publication statusPublished - 28 Sept 2012
Event35th Annual ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2012 - Portland, OR, United States
Duration: 12 Aug 201216 Aug 2012

Conference

Conference35th Annual ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2012
Country/TerritoryUnited States
CityPortland, OR
Period12/08/201216/08/2012
SponsorAssoc. Comput. Mach., Spec., Interest Group Inf. Retr. (ACM SIGIR)

Keywords

  • discourse structure
  • probabilistic retrieval model
  • rhetorical relations

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