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FGCN
2008
IEEE
130views Communications» more  FGCN 2008»
14 years 5 months ago
Word Sense Disambiguation Based on Bayes Model and Information Gain
Word sense disambiguation has always been a key problem in Natural Language Processing. In the paper, we use the method of Information Gain to calculate the weight of different po...
Zhengtao Yu, Bin Deng, Bo Hou, Lu Han, Jianyi Guo
ICARCV
2008
IEEE
184views Robotics» more  ICARCV 2008»
14 years 5 months ago
Learning informative point classes for the acquisition of object model maps
—This paper proposes a set of methods for building informative and robust feature point representations, used for accurately labeling points in a 3D point cloud, based on the typ...
Radu Bogdan Rusu, Zoltan Csaba Marton, Nico Blodow...
ICDM
2008
IEEE
127views Data Mining» more  ICDM 2008»
14 years 5 months ago
Word Sense Discovery for Web Information Retrieval
Word meaning disambiguation has always been an important problem in many computer science tasks, such as information retrieval and extraction. One of the problems, faced in automa...
Tomasz Nykiel, Henryk Rybinski
ICMCS
2007
IEEE
191views Multimedia» more  ICMCS 2007»
14 years 5 months ago
Variable Number of "Informative" Particles for Object Tracking
Particle filter is a sequential Monte Carlo method for object tracking in a recursive Bayesian filtering framework. The efficiency and accuracy of the particle filter depends on t...
Yu Huang, Joan Llach
ECAL
2007
Springer
14 years 4 months ago
Information-Cloning of Scale-Free Networks
In this paper1 , we introduce a method, Assortative Preferential Attachment, to grow a scale-free network with a given assortativeness value. Utilizing this method, we investigate ...
Piraveenan Mahendra, Mikhail Prokopenko, Albert Y....