2013
DOI: 10.1007/978-3-642-40511-2_29
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Mobile Movie Recommendations with Linked Data

Abstract: Abstract. The recent spread of the so called Web of Data has made available a vast amount of interconnected data, paving the way to a new generation of ubiquitous applications able to exploit the information encoded in it. In this paper we present Cinemappy, a location-based application that computes contextual movie recommendations. Cinemappy refines the recommendation results of a content-based recommender system by exploiting contextual information related to the current spatial and temporal position of the… Show more

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Cited by 28 publications
(18 citation statements)
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References 25 publications
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“…By inspiring from one of the ontologies used in Cinemappy by the Ostuni et al [16] and presenting information in different languages, we have obtained a faster and more consistent system because of these two ontologies come from the same origin. By using this approach, all limitations based on languages could be eliminated.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…By inspiring from one of the ontologies used in Cinemappy by the Ostuni et al [16] and presenting information in different languages, we have obtained a faster and more consistent system because of these two ontologies come from the same origin. By using this approach, all limitations based on languages could be eliminated.…”
Section: Resultsmentioning
confidence: 99%
“…Ostuni et al [16] present a mobile movie recommendation system based on Linked Data named Cinemappy which is developed for Android-based mobile devices. All information related to movies such as genres, actors, directors, etc.…”
Section: Related Workmentioning
confidence: 99%
“…More recently, two hybrid approaches have been presented: in [15] it is shown how to compute top-N recommendations from implicit feedback using linked data sources and in [10] the authors propose an event recommendation system based on linked data and user diversity. In [16] a mobile RS that uses DBpedia as the core for the recommendation is presented. Graph kernels.…”
Section: Related Workmentioning
confidence: 99%
“…Single Point of Entry Interface [15], [44], [49], [58], [54], Faceted Browsing [15], [6], Inline Resource Editing [15], [6] Customizability Living UIs [45], Providing Device-dependent UIs [49], [6], [58], [54], [5], [33], Supporting Multiple Data Sources [15], [52], [51]…”
Section: Usabilitymentioning
confidence: 99%