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KDD
2009
ACM
227views Data Mining» more  KDD 2009»
14 years 9 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
KDD
2009
ACM
174views Data Mining» more  KDD 2009»
14 years 9 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...
KDD
2009
ACM
262views Data Mining» more  KDD 2009»
14 years 9 months ago
Sentiment analysis of blogs by combining lexical knowledge with text classification
The explosion of user-generated content on the Web has led to new opportunities and significant challenges for companies, that are increasingly concerned about monitoring the disc...
Prem Melville, Wojciech Gryc, Richard D. Lawrence
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 9 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»
14 years 9 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