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Equipping Intelligent Agents with Commonsense Knowledge acquired from Search Query Logs: Results from an Exploratory Story

by: Markus Strohmaier, Mark Kröll, and Peter Prettenhofer

In: Data Mining and Multi-agent Integration (2009) , p. 167--176.

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URL:	http://dx.doi.org/10.1007/978-1-4419-0522-2_11

Access to knowledge about user goals represents a critical component for realizing the vision of intelligent agents acting upon user intent on the web. Yet, the manual acquisition of knowledge about user goals is costly and often infeasible. Ina departure from existing approaches, this paper proposes Goal Mining as a novel perspective for knowledge acquisition. Theresearch presented in this chapter makes the following contributions: a it presents Goal Mining as an emerging field of research and a corresponding automatic method for the acquisition of user goals from web corpora,in the case of this paper search query logs b it provides insights into the nature and some characteristics of these goalsand c it shows that the goals acquired from query logs exhibit traits of a long tail distribution, thereby providing accessto a broad range of user goals. Our results suggest that search query logs represent a viable, yet largely untapped resource for acquiring knowledge about explicit user goals.

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SpringerLink - Buchkapitel

BibTeX record

@incollection{strohmaier2009,
  abstract = {Access to knowledge about user goals represents a critical component for realizing the vision of intelligent agents acting
upon user intent on the web. Yet, the manual acquisition of knowledge about user goals is costly and often infeasible. Ina departure from existing approaches, this paper proposes Goal Mining as a novel perspective for knowledge acquisition. Theresearch presented in this chapter makes the following contributions: (a) it presents Goal Mining as an emerging field of research and a corresponding automatic method for the acquisition of user goals from web corpora,in the case of this paper search query logs (b) it provides insights into the nature and some characteristics of these goalsand (c) it shows that the goals acquired from query logs exhibit traits of a long tail distribution, thereby providing accessto a broad range of user goals. Our results suggest that search query logs represent a viable, yet largely untapped resource for acquiring knowledge about explicit user goals.},
  added-at = {2009-08-27T02:03:21.000+0200},
  author = {Strohmaier, Markus and Kröll, Mark and Prettenhofer, Peter},
  biburl = {http://www.bibsonomy.org/bibtex/217a8d4eeb15c1112e0253a73ce1813be/mstrohm},
  booktitle = {Data Mining and Multi-agent Integration},
  description = {SpringerLink - Buchkapitel},
  interhash = {a59825884e74d68feb0868b87df75909},
  intrahash = {17a8d4eeb15c1112e0253a73ce1813be},
  keywords = {agents goals query-log-analysis search myown},
  pages = {167--176},
  timestamp = {2009-08-27T02:03:21.000+0200},
  title = {Equipping Intelligent Agents with Commonsense Knowledge acquired from Search Query Logs: Results from an Exploratory Story },
  url = {http://dx.doi.org/10.1007/978-1-4419-0522-2_11},
  year = 2009
}

Endnote record

%0 Book Section
%1 strohmaier2009
%A Strohmaier, Markus
%A Kröll, Mark
%A Prettenhofer, Peter
%B Data Mining and Multi-agent Integration
%D 2009
%K 
%P 167--176
%T Equipping Intelligent Agents with Commonsense Knowledge acquired from Search Query Logs: Results from an Exploratory Story 
%U http://dx.doi.org/10.1007/978-1-4419-0522-2_11
%X Access to knowledge about user goals represents a critical component for realizing the vision of intelligent agents acting
upon user intent on the web. Yet, the manual acquisition of knowledge about user goals is costly and often infeasible. Ina departure from existing approaches, this paper proposes Goal Mining as a novel perspective for knowledge acquisition. Theresearch presented in this chapter makes the following contributions: (a) it presents Goal Mining as an emerging field of research and a corresponding automatic method for the acquisition of user goals from web corpora,in the case of this paper search query logs (b) it provides insights into the nature and some characteristics of these goalsand (c) it shows that the goals acquired from query logs exhibit traits of a long tail distribution, thereby providing accessto a broad range of user goals. Our results suggest that search query logs represent a viable, yet largely untapped resource for acquiring knowledge about explicit user goals.