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)
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Authors
- 1. Shenghuo Zhu
- 2. Tao Li
- 3. Zhiyuan Chen
- 4. Dingding Wang
- 5. Yihong Gong
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8 | Optimal Aggregation Algorithms for Middleware [Extended Abstract] | 2001 | PODS | 0.0015436578 |
| 386 | Shooting Stars in the Sky: An Online Algorithm for Skyline Queries | 2002 | VLDB | 0.00024740283 |
| 427 | Automated Ranking of Database Query Results | 2003 | CIDR | 0.0002350378 |
| 802 | Evaluating Top-k Selection Queries | 1999 | VLDB | 0.00016440813 |
| 1,996 | Probabilistic Ranking of Database Query Results | 2004 | VLDB | 9.8374939e-05 |
| 2,801 | Towards Keyword-Driven Analytical Processing | 2007 | SIGMOD | 8.1074407e-05 |
| 4,637 | Context-Sensitive Ranking | 2006 | SIGMOD | 6.0246358e-05 |
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