6533b825fe1ef96bd1281ca4

RESEARCH PRODUCT

Similarity Mashups for Recommendation

Arturs SosinsMartins Zviedris

subject

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

description

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.

yearjournalcountryeditionlanguage
2013-01-01
https://doi.org/10.1007/978-3-642-36403-7_9