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» Learning to learn with the informative vector machine
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NLDB
2005
Springer
15 years 10 months ago
The Role of Word Sense Disambiguation in Automated Text Categorization
Abstract. Automated Text Categorization has reached the levels of accuracy of human experts. Provided that enough training data is available, it is possible to learn accurate autom...
José María Gómez Hidalgo, Man...
CLIN
2001
15 years 5 months ago
Multi-feature Error Detection in Spoken Dialogue Systems
The present paper evaluates the role selected features and feature combinations play for error detection in spoken dialogue systems. We investigate the relevance of various, readi...
Piroska Lendvai, Antal van den Bosch, Emiel Krahme...
SIGKDD
2000
106views more  SIGKDD 2000»
15 years 4 months ago
Data mining for hypertext: A tutorial survey
With over 800 million pages covering most areas of human endeavor, the World-wide Web is a fertile ground for data mining research to make a di erence to the e ectiveness of infor...
Soumen Chakrabarti
JCIT
2010
190views more  JCIT 2010»
14 years 11 months ago
Application of Feature Extraction Method in Customer Churn Prediction Based on Random Forest and Transduction
With the development of telecom business, customer churn prediction becomes more and more important. An outstanding issue in customer churn prediction is high dimensional problem....
Yihui Qiu, Hong Li
NIPS
2003
15 years 5 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller