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» Evaluating machine learning for information extraction
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WWW
2011
ACM
14 years 11 months ago
From actors, politicians, to CEOs: domain adaptation of relational extractors using a latent relational mapping
We propose a method to adapt an existing relation extraction system to extract new relation types with minimum supervision. Our proposed method comprises two stages: learning a lo...
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuk...
CCE
2005
15 years 4 months ago
Selecting maximally informative genes
Microarray experiments are emerging as one of the main driving forces in modern biology. By allowing the simultaneous monitoring of the expression of the entire genome for a given...
Ioannis P. Androulakis
LREC
2010
174views Education» more  LREC 2010»
15 years 6 months ago
SINotas: the Evaluation of a NLG Application
SINotas is a data-to-text NLG application intended to produce short textual reports on students'academic performance from a database conveying their grades, weekly attendance...
Roberto P. A. Araujo, Rafael L. de Oliveira, Eder ...
156
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AAAI
1998
15 years 6 months ago
Modeling Web Sources for Information Integration
The Web is based on a browsing paradigm that makes it di cult to retrieve and integrate data from multiple sites. Today, the only way to do this is to build specialized applicatio...
Craig A. Knoblock, Steven Minton, José Luis...
CIKM
2005
Springer
15 years 6 months ago
Using RankBoost to compare retrieval systems
This paper presents a new pooling method for constructing the assessment sets used in the evaluation of retrieval systems. Our proposal is based on RankBoost, a machine learning v...
Huyen-Trang Vu, Patrick Gallinari