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Semantic Acquisition Games Harnessing Manpower for Creating Semantics /

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 acquisitio...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Šimko, Jakub (Autor), Bieliková, Mária (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2014.
Edición:1st ed. 2014.
Temas:
Acceso en línea:Texto Completo

MARC

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505 0 |a 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. 
520 |a 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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