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» Chunking with Support Vector Machines
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AAAI
2006
15 years 7 months ago
Kernel Methods for Word Sense Disambiguation and Acronym Expansion
The scarcity of manually labeled data for supervised machine learning methods presents a significant limitation on their ability to acquire knowledge. The use of kernels in Suppor...
Mahesh Joshi, Ted Pedersen, Richard Maclin, Sergue...
NPL
2002
103views more  NPL 2002»
15 years 6 months ago
Kernel Nearest Neighbor Algorithm
The `kernel approach' has attracted great attention with the development of support vector machine (SVM) and has been studied in a general way. It offers an alternative soluti...
Kai Yu, Liang Ji, Xuegong Zhang
ICWSM
2009
15 years 4 months ago
Delta TFIDF: An Improved Feature Space for Sentiment Analysis
Mining opinions and sentiment from social networking sites is a popular application for social media systems. Common approaches use a machine learning system with a bag of words f...
Justin Martineau, Tim Finin
INFORMATICALT
2011
91views more  INFORMATICALT 2011»
15 years 1 months ago
A Quadratic Loss Multi-Class SVM for which a Radius-Margin Bound Applies
To set the values of the hyperparameters of a support vector machine (SVM), the method of choice is cross-validation. Several upper bounds on the leave-one-out error of the pattern...
Yann Guermeur, Emmanuel Monfrini
CAIP
2007
Springer
134views Image Analysis» more  CAIP 2007»
15 years 10 months ago
An Efficient Method for Filtering Image-Based Spam E-mail
Spam e-mail with advertisement text embedded in images presents a great challenge to anti-spam filters. In this paper, we present a fast method to detect image-based spam e-mail. U...
Ngo Phuong Nhung, Tu Minh Phuong