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KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 9 months ago
Identifying bridging rules between conceptual clusters
1 A bridging rule in this paper has its antecedent and action from different conceptual clusters. We first design two algorithms for mining bridging rules between clusters in a dat...
Shichao Zhang, Feng Chen, Xindong Wu, Chengqi Zhan...
ICDE
2004
IEEE
117views Database» more  ICDE 2004»
14 years 10 months ago
Probe, Cluster, and Discover: Focused Extraction of QA-Pagelets from the Deep Web
In this paper, we introduce the concept of a QA-Pagelet to refer to the content region in a dynamic page that contains query matches. We present THOR, a scalable and efficient min...
James Caverlee, Ling Liu, David Buttler
ICDT
2009
ACM
148views Database» more  ICDT 2009»
14 years 10 months ago
Tight results for clustering and summarizing data streams
In this paper we investigate algorithms and lower bounds for summarization problems over a single pass data stream. In particular we focus on histogram construction and K-center c...
Sudipto Guha
KDD
2005
ACM
124views Data Mining» more  KDD 2005»
14 years 9 months ago
CLICKS: an effective algorithm for mining subspace clusters in categorical datasets
We present a novel algorithm called Clicks, that finds clusters in categorical datasets based on a search for k-partite maximal cliques. Unlike previous methods, Clicks mines subs...
Mohammed Javeed Zaki, Markus Peters, Ira Assent, T...
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
14 years 9 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman