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Enhancing Folksonomy-Based Content Retrieval with Semantic Web Technology

机译:借助语义Web技术增强基于Folksonomy的内容检索

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摘要

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 theinherent nature offolksonomy tags. This paper presents SemFlickr, an application which enhances the searchin 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 thoseontologies. To ensure that the highly related photos will appear at the top of the results, SemFlickr takes theontological 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 applicationsthat integrate the Semantic Web and Web 2.0 together.
机译:尽管Flickr是一个广为人知的照片共享系统,它允许用户使用标签(又名folksonomy标签)来描述自己的照片,以进行索引,但其基于标签的照片检索功能却因Folksonomy标签的固有特性而受到严重阻碍。本文介绍了SemFlickr,该应用程序通过其语义查询建议功能增强了Flickr中的搜索功能。 SemFlickr使用本体检索系统SQORE从语义Web中检索相关的本体,然后从这些本体中得出查询词建议。为了确保高度相关的照片出现在结果的顶部,SemFlickr利用给定查询词之间的本体关系来分配标签分数,然后生成其排名结果。实验结果令人鼓舞,并揭示了许多对开发应用程序有用的见解将语义Web和Web 2.0集成在一起。

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