A self-adaptive cross-domain query approach on the deep web

  • Authors:
  • Yingjun Li;Derong Shen;Tiezheng Nie;Ge Yu;Jing Shan;Kou Yue

  • Affiliations:
  • College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China

  • Venue:
  • WAIM'11 Proceedings of the 12th international conference on Web-age information management
  • Year:
  • 2011

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Abstract

As integration systems of data sources in the same domain become more and more, another application comes up with the tide of them. Because of correlation of pairs of domains, when we do some queries involving multiple domains, such as "find a post named software development engineer on job web and look for apartments for rental around the company having been chosen", we note that general-purpose search engines and general integration frameworks fail to answer cross-domain queries. This paper presents SCDQ, an approach providing fully automated support for cross-domain queries. More specifically, for SCDQ, (i) find which domains are correlated based on data sources having been clustered according to domain. (ii) Recommend different cross-domain paths to meet user's all possible intentions when query arrives.