1. 研究目的与意义
随着电子商务的飞速发展和云应用技术的普及,商业的信息化浪潮已经席卷到各行各业。
在电子商务经营中,利用数据挖掘等技术针对历史经营数据进行分析挖掘,以辅助经营决策,是企业提高收益与市场竞争力的手段之一。
电子商务以其网络化、全球化、成本低廉、方便快捷、交易透明等优点逐步发展成为成熟的商业模式。
2. 研究内容和预期目标
推荐系统的目的模拟现实生活中销售员向消费者推荐商品的过程，协助消费找到自己所满意的商品。
现有电子商务推荐算法往往是依据用户浏览行为将用户聚类，以相似用户行为作为推荐依据，这一过程忽略了用户对商品的情感态度。
而实际上，当用户对商品持积极情感时则会提高用户满意度，否则用户满意度则会降低。
3. 国内外研究现状
推荐算法方面的研究，不少研究者在这方面做了大量工作，为推动推荐系统的发展奠定了基础。
其中，有关电子商务推荐系统的文章在每年的 ACM 数据挖掘会议中所占比重逐年加大。
同时，为了推动电子商务推荐算法以及数据挖掘的发展，ACM 的 WEBKDD 研讨小组中电子商务推荐为一个重要的研讨主题。
4. 计划与进度安排
采用文献研究法，通过广泛地查阅相关资料和文献，借鉴别人研究的成果之上，深入分析、思考，形成自己的观点。
研究计划：一、收集相关资料，并对资料进行整理和深入分析二、根据资料和研究计划拟写开题报告 三、进行开题报告的答辩 四、撰写论文初稿五、对论文反复修改、定稿 六、参加论文答辩
5. 参考文献
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