一种针对社会化导购的橙领推荐方法研究

发布时间：2018-03-07 22:04

本文选题：橙领推荐　切入点：橙领定位　出处：《计算机学报》2016年10期 　论文类型：期刊论文

【摘要】：社交网络和网络购物的发展普及导致了社会化导购的产生和发展,也催生了通过在社交网络中推荐产品从而获取利润的"橙领".通过对橙领相关技术的研究,能更透彻地了解基于社会网络的产品营销机制以及探索社会化导购的底层模式.目前国内外少有这方面研究.因此,文中针对橙领的自身定位问题和面向用户或商家的橙领推荐问题,提出一种针对社会化导购的橙领推荐方法,主要包括3个算法:橙领定位算法、面向用户的橙领推荐算法OCRA4U(Orange Collar Recommending Algorithm for User)和面向商家的橙领推荐算法OCRA4S(Orange Collar Recommending Algorithm for Shop).橙领定位算法依据橙领的推荐历史对橙领进行定位特征向量化描述,最终转化为一个聚类问题进行解决.OCRA4U考虑了橙领在社交网络中的影响力和橙领与用户需求的匹配度,得到橙领推荐列表.OCRA4S结合橙领在网络中的影响力以及橙领的历史推荐产品,推荐出最符合商家产品需求的橙领列表.基于新浪微博数据集和DBLP数据集,文中设计并实现了3个相关实验:橙领定位算法实验、橙领推荐实验以及社会化数据影响实验,实验结果验证了所提算法的准确性和可行性.
[Abstract]:The popularity of social networks and online shopping has led to the emergence and development of social shopping guides, as well as the emergence of "orange collars" that make profits by recommending products on social networks. A more thorough understanding of the social network-based product marketing mechanism and explore the underlying model of socialized purchasing. At present, there is very little research in this area at home and abroad. In this paper, aiming at the problem of orange collar localization and orange collar recommendation for users or merchants, an orange collar recommendation method for socialized purchasing is proposed, which mainly includes three algorithms: orange collar location algorithm, OCRA4U(Orange Collar Recommending Algorithm for user and OCRA4S(Orange Collar Recommending Algorithm for Shop, a user-oriented orange-collar recommendation algorithm and OCRA4S(Orange Collar Recommending Algorithm for Shop, respectively. Based on the recommendation history of orange collar, the orange collar location algorithm is used to vectorize the location features of orange collar. Finally, it is transformed into a clustering problem. OCRA4U considers the influence of orange collar in social network and the matching degree between orange collar and user needs, and gets the orange collar recommendation list. OCRA4S combines the influence of orange collar in network and the historical recommendation product of orange collar. Based on Sina Weibo data set and DBLP data set, this paper designs and implements three related experiments: orange collar localization algorithm experiment, orange collar recommendation experiment and socialized data influence experiment. The experimental results verify the accuracy and feasibility of the proposed algorithm.
【作者单位】：哈尔滨工程大学计算机科学与技术学院;
【基金】：国家自然科学基金(61202090,61370084,61272184) 教育部新世纪人才支持计划(NCET-11-0829) 哈尔滨市科技创新人才基金(2015RQQXJ067) 中央高校基本科研业务费专项资金(HEUCF100602)资助~~
【分类号】：TP393.09;TP391.3

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