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A survey of diversification techniques in Recommendation Systems

机译:推荐系统中的多元化技术调查

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Recommendation Systems provide suggestions for items that are useful to a user. Initially researches in RS mainly focused to improve only accuracy of the system, however improving only accuracy does not improve user satisfaction. Recently, it has been identified that diversity is an important dimension for evaluating a recommendation system. Users find a diversified set of recommendations more interesting than a monotonous only relevance based recommendations. This paper focuses only on the diversification techniques introduced in recommendation systems. We studied papers and articles published in academic literature and categorized them into different categories. We have also highlighted trending directions that are being used to diversify recommendations.
机译:推荐系统为对用户有用的项目提供建议。最初对RS的研究主要集中于提高系统的准确性,但是仅提高准确性并不能提高用户满意度。最近,已经确定多样性是评估推荐系统的重要方面。与单调的仅基于相关性的建议相比,用户发现多样化的建议集更有趣。本文仅关注推荐系统中引入的多元化技术。我们研究了学术文献中发表的论文和文章,并将它们分为不同的类别。我们还强调了用于多样化建议的趋势指示。

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