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Titlebook: Data Engineering and Management; Second International Rajkumar Kannan,Frederic Andres Conference proceedings 2012 Springer-Verlag GmbH Berl

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https://doi.org/10.1007/978-1-4613-8593-6ntain noisy data and randomly selected initial centre of the clusters converge the clustering to local minima. In this paper, we propose a framework for clustering high dimensional data with attribute subset selection and efficient cluster centre initialization. It uses rough set theory to determine
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Overview of Hardware and Softwarering techniques to retrieve images similar to the input image. This paper involves retrieving images from huge image databases which are visually similar to a query image. Due to the enormous increase in image database size, and its high usage in a variety of applications, need for the development o
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https://doi.org/10.1007/978-1-4613-8593-6. If, for example, two different sources provide separate case reports related to the same incident, the dates of onset may not match perfectly but are more likely to differ by a few days than by several years. In order to tackle the variations in numbers a few methods are available. The paper propo
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G. Leclercq,S. Toma,J. C. Heusonalysis and Hidden Markov Model. Face recognition is an important research problem spanning numerous fields and disciplines. Face recognition draws a complex task and the changes in incident illumination ,head pose, facial expression, size and other external factors. HMM based framework for face reco
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G. Leclercq,S. Toma,J. C. Heusonedicated to this field and valuable progress has been observed. Both sequential and structured pattern mining techniques were applied to NMS. In particular NMS logs (Performance and Alarm) pose several interesting issues for pattern mining, and it can help in various NMS activities such as alarm cor
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Luigi Cancrini,Francesca Romana De Gregorioalgorithm using FP tree has been considered for frequent pattern mining because of its enormous performance and development compared to the candidate generation model of Apriori. The purpose of our work is to provide a tree structure for incremental and interactive weighted pattern mining by only on
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https://doi.org/10.1007/978-3-642-27872-3association rules; formal methods; model checking; opinion mining; wireless sensor networks
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