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Intelligent media indexing and television recommender systems

机译:智能介质索引和电视推荐系统

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This paper presents a state-of-art review on recommender systems that has been identified as possible areas of my research. It describes the current generation of collaborative filtering methods which are usually classified into three main categories: item-based, user-based and hybrid methods. The paper considers these methods to be applied to digital television providing recommendation for viewers. Personalised television is predicted to be the next step in the evolution of television which might reshape the whole landscape of mass media. The paper also identifies anticipated problems in the domain of recommender systems which includes indexing, collaborative filtering, ranking problems and possible research directions to solve these problems. Finally, these challenges are considered in the domain of personalised television which has its own inherent shortcomings.
机译:本文对推荐系统提供了最先进的综述,这些系统已被确定为我的研究可能的领域。它描述了当前的协同过滤方法的生成,这些方法通常被分类为三个主要类别:基于项目的,基于用户的和混合方法。本文认为这些方法适用于数字电视,为观众提供建议。预计个性化电视是电视演变的下一步,这可能重塑了大众媒体的整个景观。本文还识别推荐系统领域的预期问题,包括索引,协作过滤,排名问题和可能的研究方向来解决这些问题。最后,在个性化电视领域中考虑了这些挑战,其具有自己固有的缺点。

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