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In this paper we propose a two-stage algorithm for robust K-subspaces recovery. In the first stage, a large number of local candidate subspaces are generated by probabilistic farthest insertion, and then the initial near-optimal K-subspaces are solved by combinatorial selection with randomized greedy method. In the second stage, the K-subspaces are further refined by assigning each data vector to...
Glossoscopy is an important part of Traditional Chinese Medicine (TCM). To analyze the tongue properties objectively, we need extract the tongue region from images. This paper presents a method to segment the tongue images based on kernel FCM (Fuzzy Cluster means). Firstly we pre-processed the tongue images by gray-level integral projection. Secondly the features were extracted to form a feature vector...
As the lifeblood of the electric power system, the fault of transmission lines directly threaten the safe operation of the power system. Thus, effective and accurate fault prediction and positioning analysis of transmission lines, has important practical value and economic significance to the security of the power system. To solve the asymmetry of transmission line fault problem, the paper proposes...
Communities play an important role in the field of graph structure, especially in domains of networks analysis. A community (also referred to as a cluster) is a dense subgraph of the whole graph with more links between its members than between its members to the outside nodes. Communities overlap when nodes in graph belongs to multiple communities. Overlapping community detection is developing in...
Kinds of topics and discussions come forth in Web forums every day, we can talk about newsletters and daily trivial matters in virtual communities, communicate with each other deeply in thought essentially. Part subjects are hot topics, which attract a lot of users, are widely viewed and massively discussed. Hot topic can be classified as isolated topic and social topic. The characteristics of social...
Outlier detection is a hot topic of data mining. After analyzing current detection technologies, a detection method of outlier based on clustering analysis is proposed, in which an effective sample is screened out from original data. According to agglomerative of hierarchical clustering, credible sample set is found. Then mathematical expectation and standard deviation are obtained by credible sample...
Outlier detection is a hot topic of data mining. After studying the existing classical algorithms of detecting outlier, this paper proposes an outlier mining algorithm based on confidence interval, and makes a new definition for outlier. The method combines mathematical statistics and density-based clustering algorithm. It clustering firstly with DBSCAN algorithm, obtains credible sample and suspicious...
Outlier detection is a hot topic of data mining. After studying the existing classical algorithms of detecting outliers, this paper proposes an outlier mining algorithm based on probability, and makes a new definition for outlier. It clusterings firstly with density-based algorithm, and determines suspicious outlier. Then, outlier will be detected according to probability. The experiment results on...
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