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A systematic review of scholar context-aware recommender systems

机译：对学者情境感知推荐系统的系统评价

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摘要

Incorporating contextual information in recommender systems is an effective approach to create more accurate and relevant recommendations. This review has been conducted to identify the contextual information and methods used for making recommendations in digital libraries as well as the way researchers understood and used relevant contextual information from the years 2001 to 2013 based on the Kitchen-ham systematic review methodology. The results indicated that contextual information incorporated into recommendations can be categorised into three contexts, namely users' context, document's context, and environment context. In addition, the classical approaches such as collaborative filtering were employed more than the other approaches. Researchers have understood and exploited relevant contextual information through four ways, including citation of past studies, citation of past definitions, self-definitions, and field-query researches; however, citation of the past studies has been the most popular method. This review highlights the need for more investigations on the concept of context from user viewpoint in scholarly domains. It also discusses the way a context-aware recommender system can be effectively designed and implemented in digital libraries. Additionally, a few recommendations for future investigations on scholarly recommender systems are proposed.
机译：将上下文信息整合到推荐系统中是创建更准确和相关建议的有效方法。进行此项审查的目的是确定基于信息的信息和数字图书馆中用于推荐的方法，以及研究人员基于Kitchen-ham系统评价方法从2001年至2013年理解和使用相关的信息的方式。结果表明，合并到建议中的上下文信息可以分为三个上下文，即用户上下文，文档上下文和环境上下文。此外，比其他方法更多地采用了经典方法，例如协作过滤。研究人员已经通过四种方式来理解和利用相关的上下文信息，包括对过去研究的引用，对过去定义的引用，自定义和现场查询研究。但是，引用过去的研究一直是最受欢迎的方法。这篇评论强调了需要从学术领域中的用户角度对上下文的概念进行更多的研究。它还讨论了可以在数字图书馆中有效设计和实现上下文感知推荐系统的方法。此外，还提出了一些建议，以便将来对学术推荐系统进行研究。

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