Adapting Document Ranking to Users' Preferences Using Click-Through Data

  title={Adapting Document Ranking to Users' Preferences Using Click-Through Data},
  author={Min Zhao and Hang Li and Adwait Ratnaparkhi and Hsiao-Wuen Hon and Jue Wang},
  • Min Zhao, Hang Li, +2 authors Jue Wang
  • Published in AIRS 2006
  • Computer Science
  • This paper proposes a new approach to ranking the documents retrieved by a search engine using click-through data. The goal is to make the final ranked list of documents accurately represent users’ preferences reflected in the click-through data. Our approach combines the ranking result of a traditional IR algorithm (BM25) with that given by a machine learning algorithm (Naive Bayes). The machine learning algorithm is trained on click-through data (queries and their associated documents), while… CONTINUE READING

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