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Combining interaction and content for feedback-based ranking

  • Emanuele Di Buccio*
  • , Massimo Melucci
  • , Dawei Song
  • *此作品的通讯作者
  • University of Padua
  • Robert Gordon University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

The paper is concerned with the design and the evaluation of the combination of user interaction and informative content features for implicit and pseudo feedback-based document re-ranking. The features are observed during the visit of the top-ranked documents returned in response to a query. Experiments on a TREC Web test collection have been carried out and the experimental results are illustrated. We report that the effectiveness of the combination of user interaction for implicit feedback depends on whether document re-ranking is on a single-user or a user-group basis. Moreover, the adoption of document re-ranking on a user-group basis can improve pseudo-relevance feedback by providing more effective document for expanding queries.

源语言英语
主期刊名Multidisciplinary Information Retrieval - Second Information Retrieval Facility Conference, IRFC 2011, Proceedings
页46-61
页数16
DOI
出版状态已出版 - 2011
已对外发布是
活动2nd Information Retrieval Facility Conference, IRFC 2011 - Vienna, 奥地利
期限: 6 6月 2011 → 6 6月 2011

丛书

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷6653 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议2nd Information Retrieval Facility Conference, IRFC 2011
国家/地区奥地利
市Vienna
时期6/06/11 → 6/06/11

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