Skip to main content
SpringerLink
Log in

Reformulating natural language queries using sequence-to-sequence models

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

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

References

  1. Riezler S, Liu Y. Query rewriting using monolingual statistical machine translation. Comput Linguist, 2010, 36: 569–582

    Article  Google Scholar 

  2. Jones R, Rey B, Madani O, et al. Generating query substitutions. In: Proceedings of the 15th International Conference on World Wide Web, Edinburgh, 2006. 387–396

  3. Gao J F, He X D, Xie S S, et al. Learning lexicon models from search logs for query expansion. In: Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Jeju Island, 2013. 666–676

  4. Song H J, Kim A, Park S B. Translation of natural language query into keyword query using a RNN encoderdecoder. In: Proceedings of International ACM SIGIR Conference, 2017. 965–968

  5. Bahdanau D, Cho K, Bengio Y. Neural machine translation by jointly learning to align and translate. 2015. ArXiv: 1409.0473v6

  6. Luong M T, Pham H, Manning C D. Effective approaches to attention-based neural machine translation. 2015. ArXiv: 1508.04025

  7. Gu J, Lu Z, Li H, et al. Incorporating copying mechanism in sequence-to-sequence learning. 2016. ArXiv: 1603.06393

  8. Riezler S, Liu Y, Vasserman A. Translating queries into snippets for improved query expansion. In: Proceedings of International Conference on Computational Linguistics, Manchester, 2008. 737–744

  9. Rush A M, Chopra S, Weston J. A neural attention model for abstractive sentence summarization. 2015. ArXiv: 1509.00685

Download references

Acknowledgements

This work was partially supported by National Key Research and Development Plan (Grant No. 2017YFB1002104), National Natural Science Foundation of China (Grant Nos. 61532011, 61751201, 61473092, 61472088), and STCSM (Grant No. 16JC1420401, 17JC1420200). The authors would like to thank the anonymous reviewers for their helpful comments.

Author information

Authors and Affiliations

  1. School of Computer Science, Fudan University, Shanghai, 201203, China

    Xiaoyu Liu, Shunda Pan, Qi Zhang, Yu-Gang Jiang & Xuanjing Huang

Authors
  1. Xiaoyu Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shunda Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qi Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yu-Gang Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xuanjing Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Qi Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, X., Pan, S., Zhang, Q. et al. Reformulating natural language queries using sequence-to-sequence models. Sci. China Inf. Sci. 62, 229103 (2019). https://doi.org/10.1007/s11432-018-9479-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11432-018-9479-3

Search

Navigation