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KDD
2006
ACM
180views Data Mining» more  KDD 2006»
16 years 2 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
KDD
2009
ACM
174views Data Mining» more  KDD 2009»
16 years 2 months ago
Audience selection for on-line brand advertising: privacy-friendly social network targeting
This paper describes and evaluates privacy-friendly methods for extracting quasi-social networks from browser behavior on user-generated content sites, for the purpose of finding ...
Foster J. Provost, Brian Dalessandro, Rod Hook, Xi...
EDBT
2011
ACM
199views Database» more  EDBT 2011»
14 years 5 months ago
Finding closed frequent item sets by intersecting transactions
Most known frequent item set mining algorithms work by enumerating candidate item sets and pruning infrequent candidates. An alternative method, which works by intersecting transa...
Christian Borgelt, Xiaoyuan Yang, Rubén Nog...
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
16 years 2 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
16 years 2 months ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee