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IJCAI
2003
14 years 1 months ago
Integrating Background Knowledge Into Text Classification
We present a description of three different algorithms that use background knowledge to improve text classifiers. One uses the background knowledge as an index into the set of tra...
Sarah Zelikovitz, Haym Hirsh
NIPS
2004
14 years 1 months ago
Breaking SVM Complexity with Cross-Training
We propose to selectively remove examples from the training set using probabilistic estimates related to editing algorithms (Devijver and Kittler, 1982). This heuristic procedure ...
Gökhan H. Bakir, Léon Bottou, Jason We...
FLAIRS
2004
14 years 1 months ago
Combining Methods for Word Sense Disambiguation of WordNet Glosses
This paper presents a new approach for combining different semantic disambiguation methods that are part of a Word Sense Disambiguation(WSD) system. The way these methods are comb...
Adrian Novischi
EACL
2006
ACL Anthology
14 years 1 months ago
Example-Based Metonymy Recognition for Proper Nouns
Metonymy recognition is generally approached with complex algorithms that rely heavily on the manual annotation of training and test data. This paper will relieve this complexity ...
Yves Peirsman
SDM
2007
SIAM
85views Data Mining» more  SDM 2007»
14 years 1 months ago
Kernel Based Detection of Mislabeled Training Examples
The problem of identifying mislabeled training examples has been examined in several studies, with a variety of approaches developed for editing the training data to obtain better...
Hamed Valizadegan, Pang-Ning Tan
IJCAI
2007
14 years 1 months ago
Explanation-Based Feature Construction
Choosing good features to represent objects can be crucial to the success of supervised machine learning algorithms. Good high-level features are those that concentrate informatio...
Shiau Hong Lim, Li-Lun Wang, Gerald DeJong
EMNLP
2007
14 years 1 months ago
A Discriminative Learning Model for Coordinate Conjunctions
We propose a sequence-alignment based method for detecting and disambiguating coordinate conjunctions. In this method, averaged perceptron learning is used to adapt the substituti...
Masashi Shimbo, Kazuo Hara
ICDM
2007
IEEE
157views Data Mining» more  ICDM 2007»
14 years 1 months ago
Training Conditional Random Fields by Periodic Step Size Adaptation for Large-Scale Text Mining
For applications with consecutive incoming training examples, on-line learning has the potential to achieve a likelihood as high as off-line learning without scanning all availabl...
Han-Shen Huang, Yu-Ming Chang, Chun-Nan Hsu
AUSAI
2008
Springer
14 years 2 months ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan
FLAIRS
2007
14 years 2 months ago
A Distance-Based Over-Sampling Method for Learning from Imbalanced Data Sets
Many real-world domains present the problem of imbalanced data sets, where examples of one classes significantly outnumber examples of other classes. This makes learning difficu...
Jorge de la Calleja, Olac Fuentes