IPTV视频个性化推荐方案

doi:10.11959/j.issn.1000-0801.2017318

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G203

Hongyong YU,Chenxu QIU,Jianfeng WEN. IPTV video personalized recommendation system[J]. Telecommunications Science, 2017, 33(12): 127-135.

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[1]	卫星参数网. 我国有线电视付费用户跌破了1.6亿户[EB/OL].(2017-08-16)[2017-09-26]. .
	Satellite Parameter com. China’s cable TV subscribers fell 160 million households[EB/OL].(2017-08-16)[2017-09-26]. .
[2]	智库百科. DIKW 模型[EB/OL].(2016-07-27)[2017-09-20]. .
	MBA Lib. Data-to-information-to-knowledge-to-wisdom model[EB/OL].(2016-07-27)[2017-09-20]. .
[3]	尤海浪, 钱锋, 黄祥为 ,等. 基于大数据挖掘构建游戏平台个性化推荐系统的研究与实践[J]. 电信科学, 2014,30(10): 27-32.
	YOU H L , QIAN F , HUANG X W ,et al. Research and practice of building a personalized recommendation system for mobile game platform based on big data mining[J]. Telecommunications Science, 2014,30(10): 27-32.
[4]	赵晨婷, 马春娥 . 探索推荐引擎内部的秘密[EB/OL].(2011-03-16)[2017-09-22]. .
	ZHAO C T , MA C E . Explore the secrets inside the recommendation engine[EB/OL].(2011-03-16)[2017-09-22]. .
[5]	廖建新 . 大数据技术的应用现状与展望[J]. 电信科学, 2015,31(7): 7-18.
	LIAO J X . Big data technology:current applications and prospects[J]. Telecommunications Science, 2015,31(7): 7-18.
[6]	A5站长网. Netflix每年靠它节省10亿美元这套个性化推荐系统是怎么回事?[EB/OL].[2017-09-20]. .
	Admin 5 com. How does Netflix save $1 billion a year on this personalized recommendation system?[EB/OL].[2017-09-20]. .

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数据类别	标签信息	画像描述
用户基础信息	个人信息、住址信息、用户上网信息、家庭标签、支付标签等	数据主要来自运营商ODS、DPI
内容信息	节目直播表、点播内容表及节目信息表	主要来自内容提供方，部分来自网络爬取
用户IPTV业务信息	用户套餐信息、积分数据、用户IPTV订购退订汇总信息及近期订购行为、机顶盒数量及类型	数据来自运营商ODS系统和IPTV业务平台
用户IPTV观看数据	用户开机时间、观看节目信息（包括直播和点播）历史汇总数据、近期视频观看行为数据、用户实时IPTV行为数据	数据来自IPTV业务平台

类别	用户标签	用户画像
用户家庭财产信息	核心区域、三室两厅、学区房、有车、无贷款	家庭比较富裕
套餐信息	电信全家享 399 套餐、账单代扣、无欠账、两次教育产品包订购	支付能力强，支付敏感度不高，关注儿童教育
用户IPTV业务信息	一个4K机顶盒，2个高清机顶盒	喜欢高质量节目
用户IPTV观看数据	每周开机12次，观看24 h，娱乐、体育、教育占78%，直播节目占75%	IPTV中度用户，喜欢直播，点播节目有待挖掘

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IPTV video personalized recommendation system

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