Scalable multi-dimensional user intent identification using tree structured distributions

Vinay Jethava, Liliana Calderón-Benavides, Ricardo Baeza-Yates, Chiranjib Bhattacharyya, Devdatt Dubhashi

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

10 Scopus citations

Abstract

The problem of identifying user intent has received considerable attention in recent years, particularly in the context of improving the search experience via query contextualization. Intent can be characterized by multiple dimensions, which are often not observed from query words alone. Accurate identification of Intent from query words remains a challenging problem primarily because it is extremely difficult to discover these dimensions. The problem is often significantly compounded due to lack of representative training sample. We present a generic, extensible framework for learning the multi-dimensional representation of user intent from the query words. The approach models the latent relationships between facets using tree structured distribution which leads to an efficient and convergent algorithm, FastQ, for identifying the multi-faceted intent of users based on just the query words. We also incorporated WordNet to extend the system capabilities to queries which contain words that do not appear in the training data. Empirical results show that FastQ yields accurate identification of intent when compared to a gold standard.

Original languageEnglish
Title of host publicationSIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery
Pages395-404
Number of pages10
ISBN (Print)9781450309349
DOIs
StatePublished - 2011
Externally publishedYes
Event34th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2011 - Beijing, China
Duration: 24 Jul 201128 Jul 2011

Publication series

NameSIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval

Conference

Conference34th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2011
Country/TerritoryChina
CityBeijing
Period24/07/1128/07/11

Keywords

  • Chow-liu
  • Facets
  • FastQ
  • Query intent
  • Web search
  • WordNet

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