Publication | Closed Access
The recommender system: a survey
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2020
Year
EngineeringSemantic WebSocial Recommender SystemComputational Social ScienceSocial MediaInformation RetrievalData ScienceData MiningSocial Network AnalysisKnowledge DiscoveryPersonalized SearchComputer ScienceMobile ComputingCold-start ProblemInformation Filtering SystemGroup RecommendersMobile Recommender SystemSocial ComputingBusinessCollaborative Filtering
Recommender system is a helpful tool for helping the user in cutting the time needs to find personalised products, documents, friends, places and services. In addition, the recommender system handles the century web problem: information overload. In the same time, many environments or technologies (i.e., cloud, mobile, social network) become popular today and facing the problem of large amount of information. Therefore, the researchers recognise that the recommender system is a suitable solution to this problem in those environments. This paper, reviews the recent research papers that were applied the recommender system in mobile, social network, or cloud environment. We classify these recommender systems into four groups (i.e., mobile recommender system, social recommender system, cloud recommender system and traditional (PC) recommender system) depending on technology or environment that the RS is applied in. This survey presents some compression, advantages and challenges of these types of recommender systems. Also, it will directly support researchers and professionals in their understanding of those types of recommender systems.