Declarative platform for data sourcing games

Daniel Deutch, Ohad Greenshpan, Boris Kostenko, Tova Milo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Harnessing a crowd of users for the collection of mass data (data sourcing) has recently become a wide-spread practice. One effective technique is based on games as a tool that attracts the crowd to contribute useful facts. We focus here on the data management layer of such games, and observe that the development of this layer involves challenges such as dealing with probabilistic data, combined with recursive manipulation of this data. These challenges are dificult to address using current declarative data management frameworks, and we thus propose here a novel such framework, and demonstrate its usefulness in expressing different aspects in the data management of Trivia-like games. We have implemented a system prototype with our novel data management framework at its core, and we highlight key issues in the system design, as well as our experimentations that indicate the usefulness and scalability of the approach.

Original languageEnglish
Title of host publicationWWW'12 - Proceedings of the 21st Annual Conference on World Wide Web
Pages779-788
Number of pages10
DOIs
StatePublished - 2012
Event21st Annual Conference on World Wide Web, WWW'12 - Lyon, France
Duration: 16 Apr 201220 Apr 2012

Publication series

NameWWW'12 - Proceedings of the 21st Annual Conference on World Wide Web

Conference

Conference21st Annual Conference on World Wide Web, WWW'12
Country/TerritoryFrance
CityLyon
Period16/04/1220/04/12

Keywords

  • Crowdsourcing
  • Databases
  • Games
  • Probabilistic

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