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» Feature Extraction for Machine Learning: Logic-Probabilistic...
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79
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AI
2008
Springer
15 years 4 months ago
Verbs Speak Loud: Verb Categories in Learning Polarity and Strength of Opinions
In this work we show that verbs reliably represent texts when machine learning algorithms are used to learn opinions. We identify semantic verb categories that capture essential pr...
Marina Sokolova, Guy Lapalme
74
Voted
SEMWEB
2009
Springer
15 years 4 months ago
Learning Semantic Query Suggestions
An important application of semantic web technology is recognizing human-defined concepts in text. Query transformation is a strategy often used in search engines to derive querie...
Edgar Meij, Marc Bron, Laura Hollink, Bouke Huurni...
ICALT
2005
IEEE
15 years 3 months ago
An Ontology-Based Approach to Supporting Didactics in E-Learning Systems
Recent developments in E-Learning systems aim at providing a better support for didactics-aware learning scenarios. Typically, in order to provide that support the number and comp...
Denis Helic
NIPS
2007
14 years 11 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
80
Voted
WWW
2007
ACM
15 years 10 months ago
U-REST: an unsupervised record extraction system
In this paper, we describe a system that can extract record structures from web pages with no direct human supervision. Records are commonly occurring HTML-embedded data tuples th...
Yuan Kui Shen, David R. Karger