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» Measuring the Quality of Approximated Clusterings
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VLDB
2007
ACM
93views Database» more  VLDB 2007»
16 years 2 months ago
Measuring the Structural Similarity of Semistructured Documents Using Entropy
We propose a technique for measuring the structural similarity of semistructured documents based on entropy. After extracting the structural information from two documents we use ...
Sven Helmer
133
Voted
JCSS
2002
199views more  JCSS 2002»
15 years 1 months ago
A Constant-Factor Approximation Algorithm for the k-Median Problem
We present the first constant-factor approximation algorithm for the metric k-median problem. The k-median problem is one of the most well-studied clustering problems, i.e., those...
Moses Charikar, Sudipto Guha, Éva Tardos, D...
120
Voted
ICDM
2005
IEEE
151views Data Mining» more  ICDM 2005»
15 years 7 months ago
A Framework for Semi-Supervised Learning Based on Subjective and Objective Clustering Criteria
In this paper, we propose a semi-supervised framework for learning a weighted Euclidean subspace, where the best clustering can be achieved. Our approach capitalizes on user-const...
Maria Halkidi, Dimitrios Gunopulos, Nitin Kumar, M...
99
Voted
ICDM
2003
IEEE
125views Data Mining» more  ICDM 2003»
15 years 7 months ago
Clustering Item Data Sets with Association-Taxonomy Similarity
We explore in this paper the efficient clustering of item data. Different from those of the traditional data, the features of item data are known to be of high dimensionality and...
Ching-Huang Yun, Kun-Ta Chuang, Ming-Syan Chen
SIGIR
2008
ACM
15 years 1 months ago
Towards breaking the quality curse.: a web-querying approach to web people search
Searching for people on the Web is one of the most common query types to the web search engines today. However, when a person name is queried, the returned webpages often contain ...
Dmitri V. Kalashnikov, Rabia Nuray-Turan, Sharad M...