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» An Introduction to Learning Structured Information
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IJCAI
2003
14 years 11 months ago
Hierarchical Hidden Markov Models for Information Extraction
Information extraction can be defined as the task of automatically extracting instances of specified classes or relations from text. We consider the case of using machine learni...
Marios Skounakis, Mark Craven, Soumya Ray
ACMSE
2005
ACM
15 years 3 months ago
Acquiring and delivering lessons learned for NASA scientists and engineers: a dynamic approach
Web forms are a common mechanism for collecting information online. They pose some limitations which negatively affect ease and flexibility of user interaction. These limitations ...
Swapna Gupta, J. Scott Hawker, Randy K. Smith
GECCO
2004
Springer
155views Optimization» more  GECCO 2004»
15 years 3 months ago
Genetic Network Programming with Reinforcement Learning and Its Performance Evaluation
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...
Shingo Mabu, Kotaro Hirasawa, Jinglu Hu
ML
2011
ACM
179views Machine Learning» more  ML 2011»
14 years 4 months ago
Neural networks for relational learning: an experimental comparison
In the last decade, connectionist models have been proposed that can process structured information directly. These methods, which are based on the use of graphs for the representa...
Werner Uwents, Gabriele Monfardini, Hendrik Blocke...
IADIS
2003
14 years 11 months ago
Generating Guided Tours over Indexed Information Resources
This article proposes an approach to the generation of guided tours over indexed information resources on user demand. It represents an alternative to more sophisticated hyperdocu...
Benjamin Buffereau, Pierre Duchet, Philippe Picoue...