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Semantic Acquisition Games [electronic resource] : Harnessing Manpower for Creating Semantics / by Jakub Šimko, M�aria Bielikov�a.

By: Šimko, Jakub [author.].
Contributor(s): Bielikov�a, M�aria [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Cham : Springer International Publishing : Imprint: Springer, 2014Description: IX, 141 p. 28 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319061153.Subject(s): Computer science | User interfaces (Computer systems) | Computer Science | User Interfaces and Human Computer Interaction | Information Systems Applications (incl. Internet)Additional physical formats: Printed edition:: No titleDDC classification: 005.437 | 4.019 Online resources: Click here to access online
Contents:
Introduction -- Part I Games for Semantics Acquisition -- State-of-the-art: semantics acquisition and crowdsourcing -- State-of-the-art: Semantics Acquisition Games -- Little Search Game: lightweight domain modeling -- PexAce: a method for image metadata acquisition -- CityLights: a method for music metadata validation -- Part II Designing the Semantics Acquisition Games -- State-of-the-art: design of the semantics acquisition games -- Our SAGs: design aspects and improvements -- Looking Ahead.
In: Springer eBooksSummary: Many applications depend on the effective acquisition of semantic metadata, and this state-of-the-art volume provides extensive coverage of the field of semantics acquisition games (SAGs). SAGs are a part of the crowdsourcing approach family and the authors analyze their role as tools for acquisition of resource metadata and domain models. Three case studies of SAG-based semantics acquisition methods are shown, along with other existing SAGs: 1.       the Little Search Game - a search query formulation game using negative search, serving for acquisition of lightweight semantics 2.       the PexAce - a card game acquiring annotations to images 3.       the CityLights - a SAG used for validation of music metadata. The authors also look at the SAGs from their design perspectives covering  SAG design issues and existing patterns, including several novel patterns. For solving cold start problems, a "helper artifact" scheme is presented, and for dealing with malicious player behavior, a posteriori cheating detection scheme is given. The book also presents methods for assessing information about player expertise, which can be used to make SAGs more effective in terms of useful output.
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Introduction -- Part I Games for Semantics Acquisition -- State-of-the-art: semantics acquisition and crowdsourcing -- State-of-the-art: Semantics Acquisition Games -- Little Search Game: lightweight domain modeling -- PexAce: a method for image metadata acquisition -- CityLights: a method for music metadata validation -- Part II Designing the Semantics Acquisition Games -- State-of-the-art: design of the semantics acquisition games -- Our SAGs: design aspects and improvements -- Looking Ahead.

Many applications depend on the effective acquisition of semantic metadata, and this state-of-the-art volume provides extensive coverage of the field of semantics acquisition games (SAGs). SAGs are a part of the crowdsourcing approach family and the authors analyze their role as tools for acquisition of resource metadata and domain models. Three case studies of SAG-based semantics acquisition methods are shown, along with other existing SAGs: 1.       the Little Search Game - a search query formulation game using negative search, serving for acquisition of lightweight semantics 2.       the PexAce - a card game acquiring annotations to images 3.       the CityLights - a SAG used for validation of music metadata. The authors also look at the SAGs from their design perspectives covering  SAG design issues and existing patterns, including several novel patterns. For solving cold start problems, a "helper artifact" scheme is presented, and for dealing with malicious player behavior, a posteriori cheating detection scheme is given. The book also presents methods for assessing information about player expertise, which can be used to make SAGs more effective in terms of useful output.

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