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Enhancing Folksonomy-Based Content Retrieval with Semantic Web Technology

delete2010-01-01
delete1
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AI
R
Rachanee Ungrangsi
C
Chutiporn Anutariya
V
Vilas Wuwongse
DOI：10.4018/jswis.2010010102delete
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Abstract

Abstract

En 中文
While Flickr, a widely-known photo sharing system, allows users to describe their own photos with tags (aka. folksonomy tags) for indexing purposes, its tag-based photo retrieval function is severely hampered by the inherent nature of folksonomy tags. This paper presents SemFlickr, an application which enhances the search in Flickr with its semantic query suggestion feature. SemFlickr employs SQORE, an ontology retrieval system, to retrieve relevant ontologies from the Semantic Web and then derives query term suggestions from those ontologies. To ensure that the highly related photos will appear at the top of the results, SemFlickr takes the ontological relations among the given query terms to assign tag scores and then generates its ranked results. Experimental outcomes are encouraging and reveal a number of useful insights for developing applications that integrate the Semantic Web and Web 2.0 together.
Keywords:
Folksonomy
Photo Retrieval
Semantic Media Adaptation
Semantic Web
Web 2.0
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

I
International Journal on Semantic Web and Information Systems
IF:
5.6
Papers:
471
Citations:
914

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No organization information available