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WWW
2011
ACM
12 years 12 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...
NAACL
2010
13 years 2 months ago
Minimally-Supervised Extraction of Entities from Text Advertisements
Extraction of entities from ad creatives is an important problem that can benefit many computational advertising tasks. Supervised and semi-supervised solutions rely on labeled da...
Sameer Singh, Dustin Hillard, Chris Leggetter
LREC
2008
193views Education» more  LREC 2008»
13 years 6 months ago
Eksairesis: A Domain-Adaptable System for Ontology Building from Unstructured Text
This paper describes Eksairesis, a system for learning economic domain knowledge automatically from Modern Greek text. The knowledge is in the form of economic terms and the seman...
Katia Kermanidis, Aristomenis Thanopoulos, Manolis...
COLING
2008
13 years 6 months ago
Extractive Summarization Using Supervised and Semi-Supervised Learning
It is difficult to identify sentence importance from a single point of view. In this paper, we propose a learning-based approach to combine various sentence features. They are cat...
Kam-Fai Wong, Mingli Wu, Wenjie Li
ACL
2009
13 years 2 months ago
Multi-Task Transfer Learning for Weakly-Supervised Relation Extraction
Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few see...
Jing Jiang