Optimal aggregation algorithms for middleware
Journal of Computer and System Sciences - Special issu on PODS 2001
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
IEEE Transactions on Knowledge and Data Engineering
Designing games with a purpose
Communications of the ACM - Designing games with a purpose
Improving search engines using human computation games
Proceedings of the 18th ACM conference on Information and knowledge management
Crowdsourcing systems on the World-Wide Web
Communications of the ACM
CrowdDB: answering queries with crowdsourcing
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
A cross-service travel engine for trip planning
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Pushing the boundaries of crowd-enabled databases with query-driven schema expansion
Proceedings of the VLDB Endowment
Declarative platform for data sourcing games
Proceedings of the 21st international conference on World Wide Web
Max algorithms in crowdsourcing environments
Proceedings of the 21st international conference on World Wide Web
CrowdScreen: algorithms for filtering data with humans
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
So who won?: dynamic max discovery with the crowd
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Asking the Right Questions in Crowd Data Sourcing
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
CDAS: a crowdsourcing data analytics system
Proceedings of the VLDB Endowment
CrowdER: crowdsourcing entity resolution
Proceedings of the VLDB Endowment
Deco: a system for declarative crowdsourcing
Proceedings of the VLDB Endowment
Using the crowd for top-k and group-by queries
Proceedings of the 16th International Conference on Database Theory
CrowdPlanr: Planning made easy with crowd
ICDE '13 Proceedings of the 2013 IEEE International Conference on Data Engineering (ICDE 2013)
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Recent research has shown that crowd sourcing can be used effectively to solve problems that are difficult for computers, e.g., optical character recognition and identification of the structural configuration of natural proteins. In this paper we propose to use the power of the crowd to address yet another difficult problem that frequently occurs in a daily life - answering planning queries whose output is a sequence of objects/actions, when the goal, i.e, the notion of "best output", is hard to formalize. For example, planning the sequence of places/attractions to visit in the course of a vacation, where the goal is to enjoy the resulting vacation the most, or planning the sequence of courses to take in an academic schedule planning, where the goal is to obtain solid knowledge of a given subject domain. Such goals may be easily understandable by humans, but hard or even impossible to formalize for a computer. We present a novel algorithm for efficiently harnessing the crowd to assist in answering such planning queries. The algorithm builds the desired plans incrementally, choosing at each step the 'best' questions so that the overall number of questions that need to be asked is minimized. We prove the algorithm to be optimal within its class and demonstrate experimentally its effectiveness and efficiency.