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A system for web widget discovery using semantic distance between user intent and social tags

Authors :
Xiaodi Huang
Zhenzhen Zhao
Noel Crespi
Département Réseaux et Services Multimédia Mobiles (RS2M)
Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)
Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR)
Centre National de la Recherche Scientifique (CNRS)
School of Computing and Mathematics [Albury]
Charles Sturt University [Australia]
Source :
Scopus-Elsevier, SocInfo '12 : The 4th International Conference on Social Informatics, SocInfo '12 : The 4th International Conference on Social Informatics, Dec 2012, Lausanne, Switzerland. pp.1-14, ⟨10.1007/978-3-642-35386-4_1⟩, Lecture Notes in Computer Science ISBN: 9783642353857, SocInfo

Abstract

International audience; Social interaction leverages collective intelligence through user-generated content, social networking, and social annotation. Users are enabled to enrich knowledge representation by rating, commenting, and tagging. The existing systems for service discovery make use of semantic relation among social tags, but ignore the relation between a user information need for services and tags. This paper first provides an overview of how social tagging is applied to discover contents/services. An enhanced web widget discovery model that aims to discover services mostly relevant to users is then proposed. The model includes an algorithm that quantifies the accurate relation between user intent for a service and the tags of a widget, as well as three different widget discovery schemes. Using the online service of Widgetbox.com, we experimentally demonstrate the accuracy and efficiency of our system.

Details

ISBN :
978-3-642-35385-7
ISBNs :
9783642353857
Database :
OpenAIRE
Journal :
Scopus-Elsevier, SocInfo '12 : The 4th International Conference on Social Informatics, SocInfo '12 : The 4th International Conference on Social Informatics, Dec 2012, Lausanne, Switzerland. pp.1-14, ⟨10.1007/978-3-642-35386-4_1⟩, Lecture Notes in Computer Science ISBN: 9783642353857, SocInfo
Accession number :
edsair.doi.dedup.....de7e8cb26beb5fb4433d800aaa20c2f9
Full Text :
https://doi.org/10.1007/978-3-642-35386-4_1⟩