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Classifying and Ranking: The First Step Towards Mining Inside Vertical Search Engines

  • Hang Guo
  • Jun Zhang
  • Lizhu Zhou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4653)

Abstract

Vertical Search Engines (VSEs), which usually work on specific domains, are designed to answer complex queries of professional users. VSEs usually have large repositories of structured instances. Traditional instance ranking methods do not consider the categories that instances belong to. However, users of different interests usually care only the ranking list in their own communities. In this paper we design a ranking algorithm –ZRank, to rank the classified instances according to their importances in specific categories. To test our idea, we develop a scientific paper search engine–CPaper. By employing instance classifying and ranking algorithms, we discover some helpful facts to users of different interests.

Keywords

Search Engine Ranking List Ranking Algorithm Structure Instance Important Instance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Hang Guo
    • 1
  • Jun Zhang
    • 2
  • Lizhu Zhou
    • 1
  1. 1.Computer Science & Technology Department, 100084, Tsinghua University, BeijingChina
  2. 2.IBM China Software Develop Lab, 100084, BeijingChina

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