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EMNLP
2009
13 years 6 months ago
Semi-supervised Semantic Role Labeling Using the Latent Words Language Model
Semantic Role Labeling (SRL) has proved to be a valuable tool for performing automatic analysis of natural language texts. Currently however, most systems rely on a large training...
Koen Deschacht, Marie-Francine Moens
BMCBI
2008
131views more  BMCBI 2008»
13 years 8 months ago
K-OPLS package: Kernel-based orthogonal projections to latent structures for prediction and interpretation in feature space
Background: Kernel-based classification and regression methods have been successfully applied to modelling a wide variety of biological data. The Kernel-based Orthogonal Projectio...
Max Bylesjö, Mattias Rantalainen, Jeremy K. N...
ICDAR
2011
IEEE
12 years 8 months ago
A Handwritten Character Extraction Algorithm for Multi-language Document Image
—In this paper, we propose a novel method for extracting handwritten characters from multi-language document images, which may contain various types of characters, e.g. Chinese, ...
Yonghong Song, Guilin Xiao, Yuanlin Zhang, Lei Yan...
IPM
2008
159views more  IPM 2008»
13 years 8 months ago
Exploring syntactic structured features over parse trees for relation extraction using kernel methods
Extracting semantic relationships between entities from text documents is challenging in information extraction and important for deep information processing and management. This ...
Min Zhang, Guodong Zhou, AiTi Aw
ICPR
2010
IEEE
13 years 6 months ago
Scene Classification Using Spatial Pyramid of Latent Topics
We propose a scene classification method, which combines two popular methods in the literature: Spatial Pyramid Matching (SPM) and probabilistic Latent Semantic Analysis (pLSA) mod...
Emrah Ergul, Nafiz Arica