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Title:
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A NEW DENSITY-BASED CLUSTERING APPROACH IN GRAPH THEORETIC CONTEXT |
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Author(s):
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Tülin ?nkaya, Sinan Kayal?gil, Nur Evin Özdemirel |
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ISBN:
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978-972-8939-23-6 |
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Editors:
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António Palma dos Reis and Ajith P. Abraham |
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Year:
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2010 |
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Edition:
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Single |
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Keywords:
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Clustering, density, graph, arbitrary shapes, outlier. |
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Type:
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Full Paper |
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First Page:
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3 |
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Last Page:
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11 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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We consider the clustering problem with arbitrary shapes and different densities both within and between the clusters, where the number of clusters is unknown. We propose a new density-based approach in the graph theory context. The proposed algorithm has three phases. The first phase makes use of graph-based and density-based clustering approaches in order to identify the neighborhood structure of data points. The second phase detects outliers using the local outlier concept. In the third phase, a hiearchical agglomeration is performed to form the final clusters. The algorithm is tested on a number data sets and found to be effective. |
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