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LREC
2008
110views Education» more  LREC 2008»
13 years 6 months ago
Cost-Sensitive Learning in Answer Extraction
One problem of data-driven answer extraction in open-domain factoid question answering is that the class distribution of labeled training data is fairly imbalanced. This imbalance...
Michael Wiegand, Jochen L. Leidner, Dietrich Klako...
ICDAR
2009
IEEE
13 years 3 months ago
Using Kernel Density Classifier with Topic Model and Cost Sensitive Learning for Automatic Text Categorization
This paper proposes a novel framework for automatic text categorization problem based on the kernel density classifier. The overall goal is to tackle two main issues in automatic ...
Dwi Sianto Mansjur, Ted S. Wada, Biing-Hwang Juang
ICDCS
2002
IEEE
13 years 10 months ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
FSKD
2006
Springer
190views Fuzzy Logic» more  FSKD 2006»
13 years 9 months ago
A Maximum Entropy Model Based Answer Extraction for Chinese Question Answering
We regard answer extraction of Question Answering (QA) system as a classification problem, classifying answer candidate sentences into positive or negative. To confirm the feasibil...
Ang Sun, Minghu Jiang, Yanjun Ma
EMNLP
2004
13 years 6 months ago
Instance-Based Question Answering: A Data-Driven Approach
Anticipating the availability of large questionanswer datasets, we propose a principled, datadriven Instance-Based approach to Question Answering. Most question answering systems ...
Lucian Vlad Lita, Jaime G. Carbonell