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计算机系统应用英文版:2011,20(7):26-30,105
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长尾理论视角下基于DCA 的网络自助出版推荐系统
(复旦大学 文献信息中心,上海 200433)
Recommendation System Based on DCA in Web Self-Publication
(Document and Information Center, Fudan University, Shanghai 200433, China)
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Received:December 05, 2010    Revised:January 15, 2011
中文摘要: 随着自助出版系统文本规模的迅速增长,选用合理的推荐技术有利于“长尾”文本的发掘和价值实现。针对自助出版文本,设计了基于有向图的聚类算法DCA(Directed Graph Clustering Algorithm),将聚类看成是确定对象的过程,根据词间信息传递量的大小选定特征词集对文本进行聚类。为改善“长尾”文本聚类的有效性,文中所述系统设置了浮动相似度阙值及推荐公共池。实验结果表明,较之K-Means 算法,该算法有较强的自适应性和通用性,能有效地运用到自助出版文本的个性化推荐系统领域。
Abstract:To deal with the self-publication system’s huge text scale and speedy increasing, a right recommendation technology is helpful to realize the market value of “Long Tail” books. To deal with this issue, Directed Graph Clustering Algorithm is presented. Regarding clustering as the process of objects identifying, key words’ election depends on how much information they transfer in context. Moreover, to improve the efficiency of “Long Tail” texts’ clustering, a floating threshold and a sharing pool are set. Finally, experimental results comparing the K-Means algorithm prove that this clustering algorithm based on the directed graph is self-adaptive and effective.
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刘晨晨,徐一新.长尾理论视角下基于DCA 的网络自助出版推荐系统.计算机系统应用,2011,20(7):26-30,105
LIU Chen-Chen,LIU Chen-Chen.Recommendation System Based on DCA in Web Self-Publication.COMPUTER SYSTEMS APPLICATIONS,2011,20(7):26-30,105