Abstract

With the development of information technology, users usually suffer from the problem of information overload. To solve this problem, recommendation systems (RSs) are widely explored to help the user find potential interest in the overloaded information. Since the recommendation scenarios become more and more abundant, distinct recommendation tasks are accordingly proposed by the researchers. In this survey, we comprehensively investigate various recommendation domains and scenarios, and provide a classification scheme for RSs, aiming to have considerable insight for further research. This survey is supposed to give a systematic understanding of the key components in RSs and summarize the diversified characteristics in each domain or scenario.

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