Clustering with qualitative information
نویسندگان
چکیده
منابع مشابه
Clustering with Qualitative Information
We consider the problem of clustering a collection of elements based on pairwise judgments of similarity and dissimilarity. Bansal, Blum and Chawla [1] cast the problem thus: given a graph G whose edges are labeled “+” (similar) or “−” (dissimilar), partition the vertices into clusters so that the number of pairs correctly (resp. incorrectly) classified with respect to the input labeling is max...
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The Correlation Clustering problem, also known as the Cluster Editing problem, seeks to edit a given graph by adding and deleting edges to obtain a collection of vertex-disjoint cliques, such that the editing cost is minimized. The Edge Clique Partitioning problem seeks to partition the edges of a given graph into edge-disjoint cliques, such that the number of cliques is minimized. Both problem...
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A fundamental issue in clustering concerns one’s ability (and limitation) to detect clusters, assuming they are built-in to the model that generates the data [1, 4]. Results for the planted partition graph models suggest that clusters can be recovered with arbitrary accuracy if sufficient data (link density) is available [2]. More recently, this problem of cluster detectability has been address...
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We consider the following general correlation-clustering problem [1]: given a graph with real edge weights (both positive and negative), partition the vertices into clusters to minimize the total absolute weight of cut positive edges and uncut negative edges. Thus, large positive weights (representing strong correlations between endpoints) encourage those endpoints to belong to a common cluster...
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ژورنال
عنوان ژورنال: Journal of Computer and System Sciences
سال: 2005
ISSN: 0022-0000
DOI: 10.1016/j.jcss.2004.10.012