We present a divide-and-merge methodology for clustering a set of objects that combines a top-down "divide" phase with a bottom-up "merge" phase. In contrast, ...
David Cheng, Santosh Vempala, Ravi Kannan, Grant W...
We consider the problem of retrieving multiple documents relevant to the single subtopics of a given web query, termed “full-subtopic retrieval”. To solve this problem we pres...
Andrea Bernardini, Claudio Carpineto, Massimiliano...
This paper compares the efficacy and efficiency of different clustering approaches for selecting a set of exemplar images, to present in the context of a semantic concept. We eval...
Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
Clustering belongs to the set of mathematical problems which aim at classification of data or objects into related sets or classes. Many different pattern clustering approaches bas...
Faezeh Ensan, Mohammad Hossien Yaghmaee, Ebrahim B...