| 属性分布相似度吸引子传播聚类算法研究 |
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| 作者姓名： | 王依章 王丽敏 韩旭明 |
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| 作者单位： | [1]吉林财经大学管理科学与信息工程学院,吉林长春130117 [2]长春工业大学软件学院,吉林长春130012 |
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| 基金项目： | 国家自然科学基金资助项目（61202306）;吉林省科技厅基金资助项目（20100507,201215119,20130522177JH）;吉林省教育厅重点规划项目（2012185）;吉林省高校新世纪优秀人才支持计划项目（2014159）;吉林财经大学青年学俊支持计划项目 |
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| 摘 要： | 传统吸引子传播聚类算法对数据类型敏感,文中提出一种改进的吸引子传播聚类算法,将JACCARD系数引入对象间属性分布相似度,并与吸引子传播聚类算法结合。仿真实验结果表明,该算法收敛速度快,聚类精度高,明显提高高维稀疏数据的聚类性能。
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| 关 键 词： | 吸引子传播聚类算法 JACCARD系数 属性分布相似度 |
A properties distribution similarity-based affinity propagation algorithm |
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| Authors: | WANG Yi-zhang WANG Li-min HAN Xu-ming |
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| Affiliation: | 1. School of Management Science and Information Engineering, J ilin University of Finance and Economics, Changchun 130117, 2. School of Software, Changchun University of Technology, Changchun 130012, China) |
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| Abstract: | The traditional affinity propagation algorithm is sensitive to the type of data. Here we propose an improved affinity propagation algorithm which is based on property distribution similarity. JACCARD is introduced into property distribution similarity, and combined with affinity propagation clustering algorithm. Simulation results show that the method is with high precision and fast convergence, and can improve the clustering properties of high-dimensional sparse data. |
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| Keywords: | affinity propagation JACCARD properties distribution similarity |
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