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111
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ICML
2008
IEEE
16 years 14 days ago
A unified architecture for natural language processing: deep neural networks with multitask learning
We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named entity...
Ronan Collobert, Jason Weston
98
Voted
ICCV
2009
IEEE
16 years 4 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
86
Voted
AUSDM
2006
Springer
144views Data Mining» more  AUSDM 2006»
15 years 3 months ago
A Characterization of Wordnet Features in Boolean Models For Text Classification
Supervised text classification is the task of automatically assigning a category label to a previously unlabeled text document. We start with a collection of pre-labeled examples ...
Trevor N. Mansuy, Robert J. Hilderman
SDM
2010
SIAM
259views Data Mining» more  SDM 2010»
15 years 1 months ago
Semi-supervised Bio-named Entity Recognition with Word-Codebook Learning
We describe a novel semi-supervised method called WordCodebook Learning (WCL), and apply it to the task of bionamed entity recognition (bioNER). Typical bioNER systems can be seen...
Pavel P. Kuksa, Yanjun Qi
118
Voted
ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
15 years 6 months ago
Semi-Supervised Sequence Labeling with Self-Learned Features
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...