| 基于混合算法的高性能推荐策略平台 |
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| 引用本文： | 雷军环.基于混合算法的高性能推荐策略平台[J].科学技术与工程,2012,12(33):8924-8928. |
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| 作者姓名： | 雷军环 |
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| 作者单位： | 1. 湖南长沙民政职业技术学院软件学院,长沙,410004
2. 中南大学软件学院,长沙,410075 |
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| 基金项目： | 国家自然科学基金资助项目(61103202) |
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| 摘 要： | 随着电子商务的发展,个性化推荐成为其中不可缺少的重要组成部分。为了解决推荐策略系统的场景算法乏力、统一接入及性能问题,设计了基于混合算法的高性能推荐策略平台。结合用户的实时页面行为、自然属性及关系链等建立多个用户兴趣度预测模型,满足了电子商务大规模、多场景的商品推荐需求,提高了电商的流量转化率。
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| 关 键 词： | 电子商务 个性化推荐 组合推荐算法 高性能 流量转化率 实时行为 |
| 收稿时间： | 7/23/2012 2:40:43 PM |
| 修稿时间： | 2012/8/10 0:00:00 |
Strategic platform based on high-performance and hybrid recommend algorithm |
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| leijunhuan.Strategic platform based on high-performance and hybrid recommend algorithm[J].Science Technology and Engineering,2012,12(33):8924-8928. |
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| Authors: | leijunhuan |
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| Institution: | 2 (School of Software,ChangSha Social Work College1,Changsha 410004,P.R.China; School of Software,Central South University2,Changsha 410075,P.R.China) |
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| Abstract: | With the development of e-commerce, personalized recommendation become a very important part. in order to solve the problem of fatigue and unified access and performance of scene algorithm of the recommended strategy system. we design the strategic platform based on high-performance and hybrid recommended algorithm. Combined with real-time behavior and natural attributes and relationship chain of the user to establish many interest prediction models, met the needs of large-scale and multi-scene goods recommended requirements, improved the e-commerce traffic conversion rate. |
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| Keywords: | e-commerce personalized recommendation combination of recommended algorithms high-performance traffic conversion rate real-time behavior |
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