The comparative study of clustering algorithms for patent citation network can provide effective help for the practical application of citation network clustering. This method extracts and constructs citation network ...
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Currently there is an active accumulation of big data in various information environments, such as social, corporate, scientific and other domains. Intensive use of big data in various fields stimulates the increased ...
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Currently there is an active accumulation of big data in various information environments, such as social, corporate, scientific and other domains. Intensive use of big data in various fields stimulates the increased interest of researchers to the development of methods and means of processing and analyzing massive data volumes with significant variety. One of the promising areas in data intensive analytics is cluster analysis, which allows to solve such problems as: reducing the dimension of the original dataset, identifying patterns, etc. In this article, the authors propose an ensemble of clustering algorithms, consisting of the basic algorithm K-means, characterized by one parameter - the distance metric between objects. For the evaluation of performance of the designed ensemble the open data archive of UCI was used.
In this paper the use of clustering algorithms for decision level data fusion is proposed Person authentication results coming from several modalities e.g. still im age speech are combined by using the fuzzy k-means (...
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In this paper the use of clustering algorithms for decision level data fusion is proposed Person authentication results coming from several modalities e.g. still im age speech are combined by using the fuzzy k-means (FKM) and the fuzzy vector quantization (FVQ) algorithms two modification of them that use fuzzy data FKMfd and FVQfd and a median radial basis function (MRBF) network The modifications of the FKM and FVQ algorithms are based on a novel fuzzy vector distance definition and they utilize the quality measure of the results that is provided by the authentication methods Simulations show that the proposed algorithms have better performance compared to classical clustering algorithms and other known fusion algorithms.
This paper deals with a new approach for complex systems modeling and control based on neural and fuzzy clustering algorithms. It aims to derive a base of local models describing the system in the whole operating doma...
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This paper leverages on the power of clustering algorithms to determine potential deficiencies in mathematics competencies of incoming first year engineering students who are graduates of the recently implemented K to...
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This paper presents a novel approach to spell checking using dictionary clustering. The main goal is to reduce the number of times distances have to be calculated when finding target words for misspellings. The method...
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This paper presents a novel approach to spell checking using dictionary clustering. The main goal is to reduce the number of times distances have to be calculated when finding target words for misspellings. The method is unsupervised and combines the application of anomalous pattern initialization and partition around medoids (PAM). To evaluate the method, we used an English misspelling list compiled using real examples extracted from the Birkbeck spelling error corpus.
clustering generally is related to classification problem. This paper used three clustering algorithm-hierarchical, K-means, and fuzzy C-means clustering- to obtain the number of cluster which finally was applied to f...
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Iterative refinement clustering algorithms (e.g. K-Means, EM) converge to one of numerous local minima. It is known that they are especially sensitive to initial conditions. We present a procedure for computing a refi...
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The evaluation of clustering algorithms is a field of Pattern Recognition still open to extensive debate. Most quality measures found in the literature have been conceived to evaluate non-overlapping clusterings, even...
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Basic aim of our study is to analyze the medical image. In computer vision, segmentationRefers to the process of partitioning a digital image into multiple regions. The goal ofSegmentation is to simplify and/or change...
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