Towards rich query interpretation: Walking back and forth for mining query templates

Ganesh Agarwal, Govind Kabra, Kevin Chen Chuan Chang

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

Abstract

We propose to mine structured query templates from search logs, for enabling rich query interpretation that recognizes both query intents and associated attributes. We formalize the notion of template as a sequence of keywords and domain attributes, and our objective is to discover templates with high precision and recall for matching queries in a domain of interest. Our solution bootstraps from small seed input knowledge to discover relevant query templates, by harnessing the wealth of information available in search logs. We model this information in a tri-partite QueST network of queries, sites, and templates. We propose a probabilistic inferencing framework based on the dual metrics of precision and recall- and we show that the dual inferencing correspond respectively to the random walks in backward and forward directions. We deployed and tested our algorithm over a real-world search log of 15 million queries. The algorithm achieved accuracy of as high as 90% (on F-measure), with little seed knowledge and even with incomplete domain schema.

Original languageEnglish (US)
Title of host publicationProceedings of the 19th International Conference on World Wide Web, WWW '10
Pages1-10
Number of pages10
DOIs
StatePublished - Jul 20 2010
Event19th International World Wide Web Conference, WWW2010 - Raleigh, NC, United States
Duration: Apr 26 2010Apr 30 2010

Publication series

NameProceedings of the 19th International Conference on World Wide Web, WWW '10

Other

Other19th International World Wide Web Conference, WWW2010
CountryUnited States
CityRaleigh, NC
Period4/26/104/30/10

Keywords

  • query attributes
  • query intents
  • query templates
  • search log mining

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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