On the Robustness of Document Re-Ranking Techniques: A Comparison of Label Propagation, KNN, and Relevance Feedback

نویسندگان

  • Yuen-Hsien Tseng
  • Chen-Yang Tsai
  • Ze-Jing Chuang
چکیده

This paper describes our work at the sixth NTCIR workshop on the subtask of C-C single language information retrieval. We compared label propagation (LP), K-nearest neighboring (KNN), and relevance feedback (RF) for document re-ranking and found that RF is a more robust technique for performance improvement, while LP and KNN are sensitive to the choice and the number of relevant documents for successful document re-ranking.

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تاریخ انتشار 2007