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141
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KDD
2008
ACM
138views Data Mining» more  KDD 2008»
16 years 4 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
134
Voted
KDD
2007
ACM
167views Data Mining» more  KDD 2007»
16 years 4 months ago
Generalized component analysis for text with heterogeneous attributes
We present a class of richly structured, undirected hidden variable models suitable for simultaneously modeling text along with other attributes encoded in different modalities. O...
Xuerui Wang, Chris Pal, Andrew McCallum
149
Voted
KDD
2007
ACM
165views Data Mining» more  KDD 2007»
16 years 4 months ago
Efficient and effective explanation of change in hierarchical summaries
Dimension attributes in data warehouses are typically hierarchical (e.g., geographic locations in sales data, URLs in Web traffic logs). OLAP tools are used to summarize the measu...
Deepak Agarwal, Dhiman Barman, Dimitrios Gunopulos...
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
16 years 4 months ago
Correlation search in graph databases
Correlation mining has gained great success in many application domains for its ability to capture the underlying dependency between objects. However, the research of correlation ...
Yiping Ke, James Cheng, Wilfred Ng
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
16 years 4 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
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