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APNOMS
2008
Springer
13 years 7 months ago
Empirical Analysis of Application-Level Traffic Classification Using Supervised Machine Learning
Accurate application traffic classification and identification are important for network monitoring and analysis. The accuracy of traditional Internet application traffic classific...
Byungchul Park, Young J. Won, Mi-Jung Choi, Myung-...
COMSUR
2008
108views more  COMSUR 2008»
13 years 5 months ago
A survey of techniques for internet traffic classification using machine learning
The research community has begun looking for IP traffic classification techniques that do not rely on `well known' TCP or UDP port numbers, or interpreting the contents of pac...
Thuy T. T. Nguyen, Grenville J. Armitage
CORR
2002
Springer
96views Education» more  CORR 2002»
13 years 5 months ago
Thumbs up? Sentiment Classification using Machine Learning Techniques
We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, w...
Bo Pang, Lillian Lee, Shivakumar Vaithyanathan
ICML
2009
IEEE
14 years 6 months ago
MedLDA: maximum margin supervised topic models for regression and classification
Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents; and existing models apply likelihoodbased...
Jun Zhu, Amr Ahmed, Eric P. Xing