A hybrid movie recommender system based on neural networks

Christina Christakou, S. Vrettos, A. Stafylopatis
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引用次数: 126

Abstract

Recently, there has been a lot of speculation among the members of the artificial intelligence community concerning the way AI can help with the problem of successful information search in the reservoirs of knowledge of Internet. Recommender systems provide a solution to this problem by giving individualized recommendations. Content-based and collaborative filtering are usually applied to predict these recommendations. A combination of the results of these two techniques is used in this work in order to construct a system that provides more precise recommendations concerning movies. The MovieLens data set was used to test the proposed hybrid system.
基于神经网络的混合电影推荐系统
最近,在人工智能社区的成员中有很多关于人工智能如何帮助解决互联网知识库中成功搜索信息的问题的猜测。推荐系统通过提供个性化的推荐来解决这个问题。基于内容的过滤和协同过滤通常用于预测这些推荐。本文将这两种技术的结果结合起来,以构建一个提供更精确的电影推荐的系统。使用MovieLens数据集对所提出的混合系统进行了测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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