12 Jul

Optimizing Search Engines using Clickthrough Data

PubDate(2002), PubPlace(SIGKDD) Author(Joachims)
keyword(SVM,Clickthrough,Pairwise preference,Learning to rank,Metasearch)

Content

Background

  • LTR based on expert-judged relevance

Contribution

  • Generation pairwise pref. using clickthrough
  • Training this binary ordering using SVM
    • By minimizing rank correlation to optimal ranking via Kendall’s
  • Meta-search (Strive) engine to compare the learned ranking function with existing methods
    • To perform unbiased comparison of different rankings with clickthrough data, rank combination method that equally presents the links from each system.

Experiment

  • As more data was used for training, the algorithm showed lower rate of error.

Future Work

Comment

The author used the search engine himself to verify his result. I may need to build metasearch engine myself, which can be useful for a variety of tasks.

Reference

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