Spatial clustering is an important research topic in spatial data mining. This paper proposes algorithm SPCTR-GML for clustering spatial polygon objects based on topological relations for GML data. In the algorithm, w...
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Data analysis tasks often require grouping of information to identify trends and associations. However, as the number of elements rises to the hundreds and thousands the cost of having a person perform the groupings u...
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Power Iteration clustering (PIC) is an applicable and scalable graph clustering algorithm using Power Iteration (PI) for embedding the graph into the low-dimensional eigenspace what makes graph clustering tractable. T...
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In this paper, detailed study has been made on the given clustering results. It defines whitenization weight functions and establishes grey measure of clustering for evaluating 2-tuple linguistic information. Such met...
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Video-based face clustering is a very important issue in face analysis. In this paper, a framework for video-based face clustering is proposed. The framework contains two steps. First, faces are detected from videos a...
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Data mining has evolved into a dynamic field essential for uncovering valuable insights within vast and complex datasets. Among its array of techniques, clustering plays a fundamental role, aiding both as an independe...
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In this paper, we focus on the problem of unsupervised clustering which allows automatic setting of optimal clusters number. We present a generalisation of the competitive agglomeration clustering algorithm firstly in...
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ISBN:
(纸本)0769507514
In this paper, we focus on the problem of unsupervised clustering which allows automatic setting of optimal clusters number. We present a generalisation of the competitive agglomeration clustering algorithm firstly introduced in [1]. This generalization is inspired by the regularization theory and suggests a new schema for using various cluster validity criteria continuously proposed in the literature. As a consequence of this generalization, we introduce new objective clustering functions, and present their associated optimal solutions. We present an application of this competitive clustering schema to color image segmentation in order to perform partial queries in the context of image retrieval by content. In this case, each pixel is represented by the color distribution in its vicinity. clustering algorithm has to incorporate an appropriate distance measure to compare feature vectors similarity.
Fuzzy C-Means (FCM) is the most commonly used clustering algorithm despite being sensitive to initial choice of the cluster centroids. To overcome this shortcoming, the present study proposes a clustering algorithm ca...
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In today's explosive growth of online text data, how to feature mine text data from a wide range of sources, cluster text data with similar features, and classify them according to their features has become a hot ...
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This paper describes a novel clustering algorithm inspired by the humoral-mediated response triggered by the adaptive immune system. The key humoral-mediated features of the algorithm include B-cell antibodies produce...
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