Passage Retrieval and Evaluation

نویسندگان

  • Courtney Wade
  • James Allan
چکیده

Information retrieval researchers have studied passage retrieval extensively, yet there is no consensus within the community about how to evaluate the results of passage retrieval experiments. This paper describes five character-level passage evaluation measures and tasks for which they may be appropriate. In the second half of the paper we compare several passage retrieval models, including a new generative mixture model that outperforms strong baselines on many of the evaluation measures discussed in part one.

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تاریخ انتشار 2005