Hierarchical dirichlet trees for information retrieval

Gholamreza Haffari, Yee Whye Teh

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

3 Citations (Scopus)

Abstract

We propose a principled probabilisitc framework which uses trees over the vocabulary to capture similarities among terms in an information retrieval setting. This allows the retrieval of documents based not just on occurrences of specific query terms, but also on similarities between terms (an effect similar to query expansion). Additionally our principled generative model exhibits an effect similar to inverse document frequency. We give encouraging experimental evidence of the superiority of the hierarchical Dirichlet tree compared to standard baselines.

Original languageEnglish
Title of host publicationNAACL HLT 2009 - Human Language Technologies
Subtitle of host publicationThe 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Conference
Pages173-181
Number of pages9
Publication statusPublished - 1 Dec 2009
EventHuman Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, NAACL HLT 2009 - Boulder, CO, United States of America
Duration: 31 May 20095 Jun 2009

Conference

ConferenceHuman Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, NAACL HLT 2009
CountryUnited States of America
CityBoulder, CO
Period31/05/095/06/09

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