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A novel travel-time based similarity measure for hierarchical clustering

文献类型：期刊论文

作者Lu, Yonggang2; Chen, Xurong1,3; Hou, Xiaoli2
刊名NEUROCOMPUTING
出版日期2016-01-15
卷号173页码:3-8
关键词Clustering Similarity measure Travel time
ISSN号0925-2312
DOI10.1016/j.neucom.2015.01.090
英文摘要The similarity measure plays an important role in agglomerative hierarchical clustering. Following the idea of gravitational clustering which treats all the data points as mass points under a hypothetical gravitational force field, we propose a novel similarity measure for hierarchical clustering. The similarity measure is based on the estimated travel time between data points under the gravitational force field: the shorter the travel time from one point to another, the larger the similarity between the two data points. To simplify the computation, the travel time between a pair of data points is estimated using the potential field produced by all the data points. Based on the new similarity measure, we also propose a new hierarchical clustering method called Travel-Time based Hierarchical Clustering (TTHC). In the TTHC method, an edge-weighted tree of all the data points is first built using the travel-time based similarity measure, and then the clustering results are derived from the edge-weighted tree directly. To evaluate the proposed TTHC method, it is compared with four other hierarchical clustering methods on six real datasets and two synthetic dataset families composed of 200 datasets. The experiments show that using the travel-time based similarity measure can improve both the robustness and the quality of hierarchical clustering. (C) 2015 Elsevier B.V. All rights reserved.
WOS关键词NETWORKS
资助项目National Natural Science Foundation of China[61272213]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000366879600002
出版者ELSEVIER SCIENCE BV
资助机构National Natural Science Foundation of China
源URL[http://119.78.100.186/handle/113462/41251]  
专题近代物理研究所_实验物理中心
通讯作者Lu, Yonggang
作者单位1.Lanzhou Univ, Lanzhou 730000, Gansu, Peoples R China
2.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Gansu, Peoples R China
3.Chinese Acad Sci, Inst Modern Phys, Lanzhou 730000, Gansu, Peoples R China
推荐引用方式
GB/T 7714		 Lu, Yonggang,Chen, Xurong,Hou, Xiaoli. A novel travel-time based similarity measure for hierarchical clustering[J]. NEUROCOMPUTING,2016,173:3-8.
APA Lu, Yonggang,Chen, Xurong,&Hou, Xiaoli.(2016).A novel travel-time based similarity measure for hierarchical clustering.NEUROCOMPUTING,173,3-8.
MLA Lu, Yonggang,et al."A novel travel-time based similarity measure for hierarchical clustering".NEUROCOMPUTING 173(2016):3-8.

入库方式： OAI收割

来源：近代物理研究所

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