Customized Digital TV System for Individuals/Communities based on Data Stream Mining

S. Shin, W. Lee
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Abstract

The switch from analog to digital broadcast television is extended rapidly. The DTV can offer multiple programming choices, interactive capabilities and so on. Moreover, with the spread of Internet, the information exchange between the communities is increasing, too. These facts lead to the new TV service environment which can offer customized TV programs to personal/community users. This paper proposes a `Customized Digital TV System for Individuals/Communities based on Data Stream Mining` which can analyze user`s pattern of TV watching behavior. Due to the characteristics of TV program data stream and EPG(electronic program guide), the data stream mining methods are employed in the proposed system. When a user is watching DTV, the proposed system can control the surrounding circumstances as using the user behavior profiles. Furthermore, the channel recommendation system on the smart phone environment is proposed to utilize the profiles widely.
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基于数据流挖掘的个人/社区定制数字电视系统
从模拟广播电视到数字广播电视的转换迅速扩展。数字电视具有多种节目选择、交互功能等特点。此外,随着互联网的普及,社区之间的信息交流也在增加。这些事实导致了新的电视服务环境,可以为个人/社区用户提供定制的电视节目。本文提出了一种“基于数据流挖掘的个人/社区数字电视定制系统”,该系统可以分析用户的电视观看行为模式。针对电视节目数据流和电子节目单的特点,在系统中采用了数据流挖掘方法。当用户观看数字电视时,该系统可以利用用户行为特征来控制周围环境。在此基础上,提出了智能手机环境下的渠道推荐系统,以广泛利用这些配置文件。
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