Semi-supervised Information Extraction
- Automatic Content Extraction
- Extracting structured content-bases from natural language documents
- A Semi-supervised Information Extraction Approach
- Input : Natural Language Documents, Seed Instances
- Output : Structured Content-bases, such as RDBs or Semantic Web Ontologies
- Context Pattern Induction is based on the simple surface templates.
- Candidate Instance Extraction is based on the sequence alignment model.
- Content Assessment is based on the redundant-based assessment scheme.
- Cross-lingual Weakly-supervised Learning of Semantic Relations
- Motivation : Lack of resources for most languages
- Method : To leverage bilingual texts to learn the relation extractor for resource-poor languages without significant annotation efforts
- Demo Video
- You can download and play the demo video of the semi-supervised information extraction system for extracting an EPG content-base from here
- Publications
- Seokhwan Kim, Minwoo Jeong, Jonghoon Lee, Gary Geunbae Lee. A Cross-lingual Annotation Projection Approach for Relation Detection. Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010), pp 564-571, Beijing, Aug 2010
- Seokhwan Kim, Minwoo Jeong, Gary Geunbae Lee. A Local Tree Alignment-based Soft Pattern Matching Approach for Information Extraction. Proceedings of the North American Chapter of the Association for Computational Linguistics/Human Language Technology (NAACL HLT 2009), pp 169-172, Colorado, May 2009
- Seokhwan Kim, Minwoo Jeong, Gary Geunbae Lee. An Alignment-based Pattern Representation Model for Information Extraction. Proceedings of the 31st Annual International ACM SIGIR Conference (poster), pp 875-876, Singapore, July 2008
- Seokhwan Kim, Minwoo Jeong, Gary Geunbae Lee. Kwangil Ko, Zino Lee. An alignment-based approach to semi-supervised relation extraction including multiple arguments. Proceedings of the fourth Asian Information Retrieval Symposium (AIRS 2008), Harbin, Jan 2008
- Seokhwan Kim, Minwoo Jeong, Gary Geunbae Lee. A semi-supervised method for efficient construction of statistical spoken language understanding resources. Proceedings of the Interspeech 2007-Eurospeech, Antwerp, Aug 2007
- Contact
We are developing the automatic content extraction system for information agents. In order to reduce the cost of building requred resources for the automatic content extraction with minimal performance loss, we present a semi-supervised information extraction approach. We concentrate on improving not only the precision of the result, but also the coverage of the method.
