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基于查询意图的长尾查询推荐
  • 摘要

    查询推荐是一种提升用户搜索效率的重要工具.传统的查询推荐方法关注频度较高的查询,但对于那些频度较低的长尾查询,由于其信息的稀疏性而难以产生好的推荐效果.另外,传统的方法由于没有考虑查询意图对推荐结果的影响,故对长尾查询的推荐会受到查询中噪声单词的影响.该文提出了一种新的关于词项查询图(term-query graph)概率混合模型,该模型能够准确地发掘出用户的查询意图.另外,文中还提出了一种融合查询意图的查询推荐方法,该方法可以将新查询中单词的推荐结果按查询意图自然地融合起来,从而避免了噪声单词对推荐结果的影响.实验结果表明,通过考虑查询意图,可以显著提高长尾查询推荐的相关性.

  • 作者

    白露  郭嘉丰  曹雷  程学旗  BAI Lu  GUO Jia-Feng  CAO Lei  CHENG Xue-Qi 

  • 作者单位

    中国科学院计算技术研究所网络数据科学与工程研究中心 北京100190

  • 刊期

    2013年3期 ISTIC EI PKU

  • 关键词

    查询推荐  长尾查询  概率混合模型  查询意图  词项查询图 

参考文献
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