Proceedings of the 31st Annual ACM Symposium on Applied Computing 2016
DOI: 10.1145/2851613.2851839
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Measuring semantic distance for linked open data-enabled recommender systems

Abstract: The Linked Open Data (LOD) initiative has been quite successful in terms of publishing and interlinking data on the Web. On top of the huge amount of interconnected data, measuring relatedness between resources and identifying their relatedness could be used for various applications such as LOD-enabled recommender systems. In this paper, we propose various distance measures, on top of the basic concept of Linked Data Semantic Distance (LDSD), for calculating Linked Data semantic distance between resources that… Show more

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Cited by 43 publications
(41 citation statements)
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“…Piao et al [15] introduced another variation of the linked data semantic distance approach named Resource Similarity (Resim) that refined the original LDSD to overcome some of its weaknesses such as equal self-similarity, symmetry, and minimality. They also enhanced Resim in [20] by applying some normalization methods that rely on path occurrences in the data set. They also expanded the number of resources that participate in the semantic distance by using a property-based similarity measure for resources more than two links away.…”
Section: Related Workmentioning
confidence: 99%
“…Piao et al [15] introduced another variation of the linked data semantic distance approach named Resource Similarity (Resim) that refined the original LDSD to overcome some of its weaknesses such as equal self-similarity, symmetry, and minimality. They also enhanced Resim in [20] by applying some normalization methods that rely on path occurrences in the data set. They also expanded the number of resources that participate in the semantic distance by using a property-based similarity measure for resources more than two links away.…”
Section: Related Workmentioning
confidence: 99%
“…Além dos problemas clássicos mencionados acima, um desafio que abrange a maioria das técnicas de recomendação existentes é a necessidade de se considerar informações semânticas sobre itens e usuários a fim de que a filtragem dos itens possa ser realizada de maneira mais significativa para os usuários. Estudos na área de sistemas de recomendação têm analisado a possibilidade de utilização de bases de conhecimento provenientes da Web dos Dados como fonte de informações, com o objetivo de reduzir a falta de informações semânticas (PASSANT, 2010a;NOIA et al, 2012;JúNIOR;MANZATO, 2015;PIAO;BRESLIN, 2016;PESKA;VOJTAS, 2015).…”
Section: Lista De Ilustraçõesunclassified
“…A nuvem LOD (Dados Abertos Conectados, do Inglês, Linked Open Data) disponibiliza diversos conjuntos de dados semânticos gratuitamente na Web em formato compreensível por máquinas, tais dados estão relacionados a diversos domínios. Os dados abertos conectados foram adotados em sistemas de recomendação para trazer uma carga semântica com o propósito de melhorar o desempenho de tais sistemas, bem como reduzir o problema de partida fria da filtragem colaborativa (PIAO; BRESLIN, 2016;MUSTO et al, 2016;PESKA;VOJTAS, 2015).…”
Section: Lista De Ilustraçõesunclassified
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