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Recommender systems survey
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DOI：10.1016/j.knosys.2013.03.012.png)
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Abstract
En 中文
Recommender systems have developed in parallel with the web. They were initially based on demographic, content-based and collaborative filtering. Currently, these systems are incorporating social information. In the future, they will use implicit, local and personal information from the Internet cif things. This article provides an overview of recommender systems as well as collaborative filtering methods and algorithms; it also explains their evolution, provides an original classification for these systems, identifies areas of future implementation and develops certain areas selected for past, present or future importance. (C) 2013 Elsevier B.V. All rights reserved.
Keywords:
Recommender systems
Collaborative filtering
Similarity measures
Evaluation metrics
Prediction
Recommendation
Hybrid
Social
Internet of things
Cold-start
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
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