Publication: Problem Event Extraction to Develop Causal Loop Representation from Texts
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Issued Date
2019
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-85080879917
Rights Holder(s)
Scopus
Bibliographic Citation
Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019. (2019), p.1-6
Suggested Citation
Pechsiri C., Keeratipranon N., Piriyakul I. Problem Event Extraction to Develop Causal Loop Representation from Texts. Proceeding - 2019 5th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Cyber Physical System, ICSITech 2019. (2019), p.1-6. doi:10.1109/ICSITech46713.2019.8987473 Retrieved from: https://hdl.handle.net/20.500.14740/5127
Author(s)
Abstract
This research aims to extract consequent problem events as a cause-effect concept pair series, from teen-drug addiction web-boards. The extracted consequent problem events benefit for a problem analysis in a solving system through a Causal Loop representation. The research has three problems; how to determine a causative/effect event concept based on a verb phrase expression with an overlap problem between causative-verb concept set and effect-verb concept set, how to determine cause-effect concept pair series from several verb phrases, and how to develop a Causal Loop representation from the extracted cause-effect concept pair series. Therefore, we apply an event rate to solve the overlap problem. We then propose using N-WordCo to determine the cause-effect concept pair series and also use a similarity score to develop the Causal Loop representation. The research results provide a high precision of the problem event extraction from the documents. © 2019 IEEE.