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Interactive Search for One of the Top-k

Summary: Interactive top-k search learns user preference from pairwise comparisons to return a top-k result with reduced output. 2D-PI achieves asymptotically optimal question counts in 2D; HD-PI and RH extend to d≥2 with guarantees on queries and runtime; experiments show fewer questions and faster results. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6274
Venue
SIGMOD
Year
2021
Pagerank
5.1997534e-05
Overall Rank
9,901 | 32.08%
DOI
10.1145/3448016.3457322

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{wang_sigmod21,
        title = {{Interactive Search for One of the Top-k}},
        author = {Wang, Weicheng and Wong, Raymond Chi-Wing and Xie, Min},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3457322},
        url = {https://dl.acm.org/doi/10.1145/3448016.3457322},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
11,250 Robust Best Point Selection under Unreliable User Feedback 2024 VLDB 5.093636e-05
11,397 rkHit: Representative Query with Uncertain Preference 2023 SIGMOD 5.093636e-05
11,576 Interactive Mining with Ordered and Unordered Attributes 2022 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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