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AI
2010
Springer
15 years 2 months ago
Supervised Machine Learning for Summarizing Legal Documents
This paper presents a supervised machine learning approach for summarizing legal documents. A commercial system for the analysis and summarization of legal documents provided us wi...
Mehdi Yousfi Monod, Atefeh Farzindar, Guy Lapalme
ICPR
2002
IEEE
15 years 11 months ago
Incorporating Conditional Independence Assumption with Support Vector Machines to Enhance Handwritten Character Segmentation Per
Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
Manolis Maragoudakis, Ergina Kavallieratou, Nikos ...
ICALT
2006
IEEE
15 years 4 months ago
Towards Effective Usage-Based Learning Applications: Track and Learn from User Experience(s)
In this paper we propose a schema and framework for recording and managing attention metadata. This framework is intended to capture, manage, and re-use data about attention users...
Jehad Najjar, Erik Duval, Martin Wolpers
BMCBI
2008
228views more  BMCBI 2008»
14 years 10 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
NIPS
2008
14 years 11 months ago
One sketch for all: Theory and Application of Conditional Random Sampling
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...
Ping Li, Kenneth Ward Church, Trevor Hastie