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147
Voted
KDD
2009
ACM
269views Data Mining» more  KDD 2009»
16 years 4 months ago
Extracting discriminative concepts for domain adaptation in text mining
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
Bo Chen, Wai Lam, Ivor Tsang, Tak-Lam Wong
163
Voted
KDD
2009
ACM
262views Data Mining» more  KDD 2009»
16 years 4 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
134
Voted
KDD
2009
ACM
296views Data Mining» more  KDD 2009»
16 years 4 months ago
Anonymizing healthcare data: a case study on the blood transfusion service
: Gaining access to high-quality health data is a vital requirement to informed decision making for medical practitioners and pharmaceutical researchers. Driven by mutual benefits ...
Noman Mohammed, Benjamin C. M. Fung, Patrick C. K....
141
Voted
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 4 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
PODS
2009
ACM
119views Database» more  PODS 2009»
16 years 4 months ago
Exceeding expectations and clustering uncertain data
Database technology is playing an increasingly important role in understanding and solving large-scale and complex scientific and societal problems and phenomena, for instance, un...
Sudipto Guha, Kamesh Munagala
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