Corpus ID: 219559030

ORCAS: 18 Million Clicked Query-Document Pairs for Analyzing Search

@article{Craswell2020ORCAS1M,
  title={ORCAS: 18 Million Clicked Query-Document Pairs for Analyzing Search},
  author={Nick Craswell and Daniel Fernando Campos and Bhaskar Mitra and E. Yilmaz and Bodo Billerbeck},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.05324}
}
  • Nick Craswell, Daniel Fernando Campos, +2 authors Bodo Billerbeck
  • Published 2020
  • Computer Science
  • ArXiv
  • Users ofWeb search engines reveal their information needs through queries and clicks, making click logs a useful asset for information retrieval. However, click logs have not been publicly released for academic use, because they can be too revealing of personally or commercially sensitive information. This paper describes a click data release related to the TREC Deep Learning Track document corpus. After aggregation and filtering, including a k-anonymity requirement, we find 1.4 million of the… CONTINUE READING

    Figures and Tables from this paper.

    Conformer-Kernel with Query Term Independence for Document Retrieval
    1

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 30 REFERENCES
    Learning to personalize query auto-completion
    139
    Learning deep structured semantic models for web search using clickthrough data
    981
    Optimizing web search using web click-through data
    273
    Query suggestion using hitting time
    319
    Overview of the TREC 2019 deep learning track
    26
    Random walks on the click graph
    477
    Recent and robust query auto-completion
    62
    Learning to Match using Local and Distributed Representations of Text for Web Search
    242