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103
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PKDD
1999
Springer
90views Data Mining» more  PKDD 1999»
15 years 8 months ago
Learning from Highly Structured Data by Decomposition
This paper addresses the problem of learning from highly structured data. Speci cally, it describes a procedure, called decomposition, that allows a learner to access automatically...
René MacKinney-Romero, Christophe G. Giraud...
ESANN
2008
15 years 5 months ago
Word recognition and incremental learning based on neural associative memories and hidden Markov models
Abstract. An architecture for achieving word recognition and incremental learning of new words in a language processing system is presented. The architecture is based on neural ass...
Zöhre Kara Kayikci, Günther Palm
168
Voted
ACL
1997
15 years 5 months ago
Learning Parse and Translation Decisions from Examples with Rich Context
We present a knowledge and context-based system for parsing and translating natural language and evaluate it on sentences from the Wall Street Journal. Applying machine learning t...
Ulf Hermjakob, Raymond J. Mooney
CORR
2007
Springer
88views Education» more  CORR 2007»
15 years 3 months ago
A software for learning Information Theory basics with emphasis on Entropy of Spanish
In this paper, an educational software aimed to help learning Information Theory basics in a practical way is reported. The software, called IT-tutor-UV, can produce entropy analy...
Fabio G. Guerrero, Lucio A. Perez
133
Voted
ICTAI
2007
IEEE
15 years 10 months ago
Dragon Toolkit: Incorporating Auto-Learned Semantic Knowledge into Large-Scale Text Retrieval and Mining
The majority of text retrieval and mining techniques are still based on exact feature (e.g. words) matching and unable to incorporate text semantics. Many researchers believe that...
Xiaohua Zhou, Xiaodan Zhang, Xiaohua Hu