On Designing an Effective Training Set for Information Extraction
- Title
- On Designing an Effective Training Set for Information Extraction
- Author
- 김영민
- Keywords
- Training set; Information Extraction; Relation & Event Extraction
- Issue Date
- 2015-01
- Publisher
- Springer
- Citation
- Lecture Notes in Electrical Engineering, v. 330, page. 1101-1107
- Abstract
- While training set design has received less attention from academia compared to its significance, it becomes crucial in big data environments. We propose a novel way to construct a training set for information extraction. An effective data collection considering the trade-off between system quality and annotation difficulty is the core of the proposed approach. Instead of a random collection of data like usual systems, well-defined key expressions are used as sampling queries. This work is a part of an on-going R&D project and now in process of manual annotation that would be evaluated via final system quality.
- URI
- http://hdl.handle.net/20.500.11754/23277https://link.springer.com/chapter/10.1007/978-3-662-45402-2_156
- ISSN
- 1876-1100
- DOI
- 10.1007/978-3-662-45402-2_156
- Appears in Collections:
- GRADUATE SCHOOL OF TECHNOLOGY & INNOVATION MANAGEMENT[S](기술경영전문대학원) > ETC
- Files in This Item:
There are no files associated with this item.
- Export
- RIS (EndNote)
- XLS (Excel)
- XML