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Answering Planning Queries with the Crowd

Summary: Leverages crowd input to answer planning queries with ill-defined objectives (sequences of actions). Proposes an incremental, best-question-first algorithm that builds plans step-by-step to minimize total queries; proves optimality within its class and demonstrates empirical efficiency. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10733
Venue
VLDB
Year
2013
Pagerank
4.8227734e-05
Overall Rank
7,112 | 50.58%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
5,744 Efficient Algorithms for Crowd-Aided Categorization 2020 VLDB 5.343155e-05
7,025 Hear the Whole Story: Towards the Diversity of Opinion in Crowdsourcing Markets 2015 VLDB 4.8530001e-05
7,224 OASSIS: Query Driven Crowd Mining 2014 SIGMOD 4.791302e-05
8,062 Where To: Crowd-Aided Path Selection 2014 VLDB 4.5902135e-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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