Knowledge Discovery from Data (TKDD)


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ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 2 Issue 2, July 2008

Joint cluster analysis of attribute data and relationship data: The connected k-center problem, algorithms and applications
Rong Ge, Martin Ester, Byron J. Gao, Zengjian Hu, Binay Bhattacharya, Boaz Ben-Moshe
Article No.: 7
DOI: 10.1145/1376815.1376816

Attribute data and relationship data are two principal types of data, representing the intrinsic and extrinsic properties of entities. While attribute data have been the main source of data for cluster analysis, relationship data such as social...

Bregman bubble clustering: A robust framework for mining dense clusters
Gunjan Gupta, Joydeep Ghosh
Article No.: 8
DOI: 10.1145/1376815.1376817

In classical clustering, each data point is assigned to at least one cluster. However, in many applications only a small subset of the available data is relevant for the problem and the rest needs to be ignored in order to obtain good clusters....

Tree model guided candidate generation for mining frequent subtrees from XML documents
Henry Tan, Fedja Hadzic, Tharam S. Dillon, Elizabeth Chang, Ling Feng
Article No.: 9
DOI: 10.1145/1376815.1376818

Due to the inherent flexibilities in both structure and semantics, XML association rules mining faces few challenges, such as: a more complicated hierarchical data structure and ordered data context. Mining frequent patterns from XML documents can...

Semantic text similarity using corpus-based word similarity and string similarity
Aminul Islam, Diana Inkpen
Article No.: 10
DOI: 10.1145/1376815.1376819

We present a method for measuring the semantic similarity of texts using a corpus-based measure of semantic word similarity and a normalized and modified version of the Longest Common Subsequence (LCS) string matching algorithm. Existing methods...