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ICDAR
2009
IEEE
13 years 6 months ago
Using Kernel Density Classifier with Topic Model and Cost Sensitive Learning for Automatic Text Categorization
This paper proposes a novel framework for automatic text categorization problem based on the kernel density classifier. The overall goal is to tackle two main issues in automatic ...
Dwi Sianto Mansjur, Ted S. Wada, Biing-Hwang Juang
ICRA
2006
IEEE
149views Robotics» more  ICRA 2006»
14 years 2 months ago
On Learning the Statistical Representation of a Task and Generalizing it to Various Contexts
— This paper presents an architecture for solving generically the problem of extracting the constraints of a given task in a programming by demonstration framework and the problem...
Sylvain Calinon, Florent Guenter, Aude Billard
SIGIR
2004
ACM
14 years 1 months ago
Locality preserving indexing for document representation
Document representation and indexing is a key problem for document analysis and processing, such as clustering, classification and retrieval. Conventionally, Latent Semantic Index...
Xiaofei He, Deng Cai, Haifeng Liu, Wei-Ying Ma
ICML
2005
IEEE
14 years 9 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
ACL
2006
13 years 9 months ago
BiTAM: Bilingual Topic AdMixture Models for Word Alignment
We propose a novel bilingual topical admixture (BiTAM) formalism for word alignment in statistical machine translation. Under this formalism, the parallel sentence-pairs within a ...
Bing Zhao, Eric P. Xing