0000000000563520

AUTHOR

Arturs Sosins

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Similarity Mashups for Recommendation

2013

Recommendation systems are becoming a state of the art for web-based systems as they produce additional product exposure and customer satisfaction. The Semantic Web and mashups can improve recommendation systems and provide new ways for their creation. In the web it is possible to analyze product descriptions and to use Linked Data for characterizing the similarity of objects or of objects and user interests. In this chapter, we give a brief overview of existing technical approaches and tools for creating recommendation systems that can be used to create mashups as recommendation systems.

World Wide WebApplication programming interfaceComputer scienceCustomer satisfactionMashupcomputer.file_formatLinked dataRDFRecommender systemcomputer.software_genreVideo gameSemantic Webcomputer
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