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ICML
2000
IEEE
14 years 9 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
WWW
2007
ACM
14 years 9 months ago
Topic sentiment mixture: modeling facets and opinions in weblogs
In this paper, we define the problem of topic-sentiment analysis on Weblogs and propose a novel probabilistic model to capture the mixture of topics and sentiments simultaneously....
Qiaozhu Mei, Xu Ling, Matthew Wondra, Hang Su, Che...
KDD
2008
ACM
209views Data Mining» more  KDD 2008»
14 years 9 months ago
Combinational collaborative filtering for personalized community recommendation
Rapid growth in the amount of data available on social networking sites has made information retrieval increasingly challenging for users. In this paper, we propose a collaborativ...
WenYen Chen, Dong Zhang, Edward Y. Chang
RECOMB
2006
Springer
14 years 9 months ago
Integrated Protein Interaction Networks for 11 Microbes
We have combined four different types of functional genomic data to create high coverage protein interaction networks for 11 microbes. Our integration algorithm naturally handles s...
Balaji S. Srinivasan, Antal F. Novak, Jason Flanni...
RECOMB
2004
Springer
14 years 9 months ago
A class of edit kernels for SVMs to predict translation initiation sites in eukaryotic mRNAs
The prediction of translation initiation sites (TISs) in eukaryotic mRNAs has been a challenging problem in computational molecular biology. In this paper, we present a new algori...
Haifeng Li, Tao Jiang