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» Hidden Maximum Entropy Approach for Visual Concept Modeling
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KDD
2005
ACM
218views Data Mining» more  KDD 2005»
14 years 5 months ago
A maximum entropy web recommendation system: combining collaborative and content features
Web users display their preferences implicitly by navigating through a sequence of pages or by providing numeric ratings to some items. Web usage mining techniques are used to ext...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
IJCNLP
2005
Springer
13 years 10 months ago
Automatic Image Annotation Using Maximum Entropy Model
Automatic image annotation is a newly developed and promising technique to provide semantic image retrieval via text descriptions. It concerns a process of automatically labeling t...
Wei Li, Maosong Sun
ICASSP
2008
IEEE
13 years 11 months ago
A GIS-like training algorithm for log-linear models with hidden variables
Conditional Random Fields (CRFs) are often estimated using an entropy based criterion in combination with Generalized Iterative Scaling (GIS). GIS offers, upon others, the immedi...
Georg Heigold, Thomas Deselaers, Ralf Schlüte...
ICML
2003
IEEE
14 years 6 months ago
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
ACL
2007
13 years 6 months ago
Automatic Part-of-Speech Tagging for Bengali: An Approach for Morphologically Rich Languages in a Poor Resource Scenario
This paper describes our work on building Part-of-Speech (POS) tagger for Bengali. We have use Hidden Markov Model (HMM) and Maximum Entropy (ME) based stochastic taggers. Bengali...
Sandipan Dandapat, Sudeshna Sarkar, Anupam Basu