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Serendipity in Recommender Systems:A Systematic Literature Review

机译:推荐系统中的Serendipity:系统文献综述

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A recommender system is employed to accurately recommend items,which are expected to attract the user''s attention.The over-emphasis on the accuracy of the recommendations can cause information over-specialization and make recommendations boring and even predictable.Novelty and diversity are two partly useful solutions to these problems.However,novel and diverse recommendations cannot merely ensure that users are attracted since such recommendations may not be relevant to the user''s interests.Hence,it is necessary to consider other criteria,such as unexpectedness and relevance.Serendipity is a criterion for making appealing and useful recommendations.The usefulness of serendipitous recommendations is the main superiority of this criterion over novelty and diversity.The bulk of studies of recommender systems have focused on serendipity in recent years.Thus,a systematic literature review is conducted in this paper on previous studies of serendipity-oriented recommender systems.Accordingly,this paper focuses on the contextual convergence of serendipity definitions,datasets,serendipitous recommendation methods,and their evaluation techniques.Finally,the trends and existing potentials of the serendipity-oriented recommender systems are discussed for future studies.The results of the systematic literature review present that the quality and the quantity of articles in the serendipity-oriented recommender systems are progressing.
机译:推荐制度用于准确推荐预期吸引用户注意的物品。过高强调建议的准确性可能导致信息过度专业化,并提出建议无聊,甚至可预测.Novelty和多样性这些问题的两个部分有用的解决方案。但是,新颖和不同的建议不能仅确保用户被吸引,因为这些建议可能与用户的兴趣不相关。因此,有必要考虑其他标准,例如意外和意外相关性是制定吸引人和有用的建议的标准。午集建议的有用性是对新颖性和多样性的本标准的主要优势。近年来,推荐系统的大部分研究都集中在黎明。,系统的文学审查是在本文中进行的,以先前的定期推荐系统进行了研究.According本文侧重于偶然定义,数据集,午集推荐方法及其评估技术的上下文收敛。最后,讨论了偶然的推荐系统的趋势和现有的潜力用于未来的研究。系统文学的结果综述显示,面向黎明的推荐系统中的文章的质量和数量正在进行中。

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