Skip to main content
Log in

A greedy selection approach for query suggestion diversification in search systems

检索系统中查询推荐的多样化方法研究

  • Letter
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

摘要

创新点

本文提出一种贪婪算法, 解决信息检索系统中查询推荐多样化问题, 算法目的旨在返回给用户的查询推荐列表既能准确包含用户的潜在查询, 又能使得查询列表涵盖尽可能多的主题, 这样提高不同类型用户查询推荐满意度。 在本算法中, 用户的查询意图不仅体现在当前查询热度上, 同时我们从用户的检索查询历史中挖掘有用信息预测用户意图, 生成用户的查询意图在各个主题上的概率分布, 并依此计算每个查询词被提交的概率并进行排序。 提出的算法在公共测试集上取得了较好地性能, 能把初始查询推荐列表中相似的查询词移除, 达到查询词多样化的目的。

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

References

  1. Shokouhi M. Learning to personalize query autocompletion. In: Proceedings of 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, Dublin, 2013. 103–112

    Google Scholar 

  2. Bar-Yossef Z, Kraus N. Context-sensitive query autocompletion. In: Proceedings of 20th International World Wide Web Conference, Hyderabad, 2011. 107–116

    Google Scholar 

  3. Shokouhi M, Radinsky K. Time-sensitive query autocompletion. In: Proceedings of 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, Portland, 2012. 601–610

    Google Scholar 

  4. Whiting S, Jose J M. Recent and robust query autocompletion. In: Proceedings of 23th International World Wide Web Conference, Seoul, 2014. 971–982

    Google Scholar 

  5. Bennett P N, Svore K, Dumais S T. Classificationenhanced ranking. In: Proceedings of 19th International World Wide Web Conference, Raleigh, 2010. 111–120

    Google Scholar 

  6. Mikolov T, Sutskever I, Chen K, et al. Distributed representations of words and phrases and their compositionality. In: Proceedings of Advances in Neural Information Processing Systems, Lake Tahoe, 2013. 3111–3119

    Google Scholar 

  7. Salakhutdinov R, Mnih A. Bayesian probabilistic matrix factorization using Markov Chain Monte Carlo. In: Proceedings of 25th International Conference on Machine Learning, Helsinki, 2008. 880–887

    Google Scholar 

  8. Carbonell J, Goldstein J. The use of MMR, diversitybased reranking for reordering documents and producing summaries. In: Proceedings of 21st International ACM SIGIR Conference on Research and Development in Information Retrieval, Melbourne, 1998. 335–336

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fei Cai.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cai, F., Chen, H. & Shu, Z. A greedy selection approach for query suggestion diversification in search systems. Sci. China Inf. Sci. 59, 119101 (2016). https://doi.org/10.1007/s11432-016-5531-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11432-016-5531-y

关键词

Navigation