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Dynamic Active Probing of Helpdesk Databases

Summary: Dynamic active probing selects minimal clarifying questions for helpdesk recommendations, using each answer to steer the next query in real time. Probabilistic model with data augmentation to resist incomplete/noisy data; robust clarifications outperform decision trees and CBR. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9902
Venue
VLDB
Year
2008
Pagerank
5.093636e-05
Overall Rank
12,581 | 13.69%
DOI
10.14778/1454159.1454167

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Authors

BibTeX Citation

@article{zhu_vldb08,
        title = {{Dynamic Active Probing of Helpdesk Databases}},
        author = {Zhu, Shenghuo and Li, Tao and Chen, Zhiyuan and Gong, Yihong and Wang, Dingding},
        journal = {PVLDB},
        series = {{VLDB} '08},
        volume = {1},
        number = {1},
        pages = {748--759},
        doi = {10.14778/1454159.1454167},
        url = {https://doi.org/10.14778/1454159.1454167},
        year = {2008}
}

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

Rank Cited Paper Year Venue Pagerank
5 Optimal Aggregation Algorithms for Middleware [Extended Abstract] 2001 PODS 0.0010828372
308 Shooting Stars in the Sky: An Online Algorithm for Skyline Queries 2002 VLDB 0.00021787597
466 Automated Ranking of Database Query Results 2003 CIDR 0.00018014467
635 Evaluating Top-k Selection Queries 1999 VLDB 0.00015527042
1,844 Probabilistic Ranking of Database Query Results 2004 VLDB 9.6314187e-05
2,784 Towards Keyword-Driven Analytical Processing 2007 SIGMOD 8.1271176e-05
4,622 Context-Sensitive Ranking 2006 SIGMOD 6.6014783e-05
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