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» Evaluating machine learning for information extraction
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NLPRS
2001
Springer
15 years 4 months ago
Hierarchical Concept Description and Learning for Information Extraction
This paper addresses the problem of extracting information from textual documents, either normal documents or web pages. A new approach for extracting complicate information from ...
Luo Xiao, Dieter Wissmann, Michael Brown, Stefan J...
WWW
2007
ACM
16 years 10 days ago
Hierarchical, perceptron-like learning for ontology-based information extraction
Recent work on ontology-based Information Extraction (IE) has tried to make use of knowledge from the target ontology in order to improve semantic annotation results. However, ver...
Yaoyong Li, Kalina Bontcheva
ICML
2008
IEEE
16 years 14 days ago
Extracting and composing robust features with denoising autoencoders
Previous work has shown that the difficulties in learning deep generative or discriminative models can be overcome by an initial unsupervised learning step that maps inputs to use...
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pi...
SIGIR
2009
ACM
15 years 6 months ago
The importance of manual assessment in link discovery
Using a ground truth extracted from the Wikipedia, and a ground truth created through manual assessment, we show that the apparent performance advantage seen in machine learning a...
Darren Wei Che Huang, Andrew Trotman, Shlomo Geva
LREC
2008
141views Education» more  LREC 2008»
15 years 1 months ago
Creating Glossaries Using Pattern-Based and Machine Learning Techniques
One of the aims of the Language Technology for eLearning project is to show that Natural Language Processing techniques can be employed to enhance the learning process. To this en...
Eline Westerhout, Paola Monachesi