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Recommender Systems: Issues, Challenges, and Research Opportunities

机译:推荐系统:问题,挑战和研究机会

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A recommender system is an Information Retrieval technology that improves access and proactively recommends relevant items to users by considering the users' explicitly mentioned preferences and objective behaviors. A recommender system is one of the major techniques that handle information overload problem of Information Retrieval by suggesting users with appropriate and relevant items. Today, several recommender systems have been developed for different domains however, these are not precise enough to fulfil the information needs of users. Therefore, it is necessary to build high quality recommender systems. In designing such recommenders, designers face several issues and challenges that need proper attention. This paper investigates and reports the current trends, issues, challenges, and research opportunities in developing high-quality recommender systems. If properly followed, these issues and challenges will introduce new research avenues and the goal towards fine-tuned and high-quality recommender systems can be achieved.
机译:推荐器系统是一种信息检索技术,它可以通过考虑用户明确提到的偏好和客观行为来改善访问范围并主动向用户推荐相关项目。推荐系统是通过向用户建议适当和相关项目来处理信息检索信息超载问题的主要技术之一。如今,已经针对不同领域开发了几种推荐系统,但是这些系统不够精确,无法满足用户的信息需求。因此,有必要构建高质量的推荐系统。在设计此类推荐器时,设计人员面临一些需要适当注意的问题和挑战。本文调查并报告了开发高质量推荐系统时的当前趋势,问题,挑战和研究机会。如果正确遵循这些问题和挑战,将会引入新的研究途径,并且可以实现微调和高质量推荐系统的目标。

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