SEQUEL: query completion via pattern mining on multi-column structural data

  • Authors:
  • Chuancong Gao;Qingyan Yang;Jianyong Wang

  • Affiliations:
  • Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China

  • Venue:
  • CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
  • Year:
  • 2010

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Abstract

In this demonstration, we propose an interactive query completion system on structural data like DBLP, called SEQUEL. It is novel in several aspects: with patterns mined on the structural data using newly devised algorithm, SEQUEL offers high-utility completions composed with not only words but also phrases, and requires no explicit indications of corresponding columns. Instead of using query logs exploited previously for unstructured data, more effective completions are provided based on patterns mined directly from the records. Moreover, an effective index structure helps SEQUEL respond fast at millisecond level for each keystroke.