Causal Pathway Extraction from Web-Board Documents
This research aim is to extract causal pathways, particularly disease causal pathways, through cause-effect relation (CErel) extraction from web-board documents. The causal pathways benefit people with a comprehensible representation approach to disease complication. A causative/effect-concept expre...
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2021
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oai:doaj.org-article:9d85ae9a915a41d680dbfdf974c53dcd2021-11-11T15:22:13ZCausal Pathway Extraction from Web-Board Documents10.3390/app1121103422076-3417https://doaj.org/article/9d85ae9a915a41d680dbfdf974c53dcd2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10342https://doaj.org/toc/2076-3417This research aim is to extract causal pathways, particularly disease causal pathways, through cause-effect relation (CErel) extraction from web-board documents. The causal pathways benefit people with a comprehensible representation approach to disease complication. A causative/effect-concept expression is based on a verb phrase of an elementary discourse unit (EDU) or a simple sentence. The research has three main problems; how to determine CErel on an EDU-concept pair containing both causative and effect concepts in one EDU, how to extract causal pathways from EDU-concept pairs having CErel and how to indicate and represent implicit effect/causative-concept EDUs as implicit mediators with comprehension on extracted causal pathways. Therefore, we apply EDU’s word co-occurrence concept (wrdCoc) as an EDU-concept and the self-Cartesian product of a wrdCoc set from the documents for extracting wrdCoc pairs having CErel into a wrdCoc-pair set from the documents after learning CErel on wrdCoc pairs by supervised-machine learning. The wrdCoc-pair set is used for extracting the causal pathways by wrdCoc-pair matching through the documents. We then propose transitive closure and a dynamic template to indicate and represent the implicit mediators with the explicit ones. In contrast to previous works, the proposed approach enables causal-pathway extraction with high accuracy from the documents.Chaveevan PechsiriRapepun PiriyakulMDPI AGarticlecause-effect relationtransitive closureword co-occurrenceTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10342, p 10342 (2021) |
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cause-effect relation transitive closure word co-occurrence Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 |
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cause-effect relation transitive closure word co-occurrence Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Chaveevan Pechsiri Rapepun Piriyakul Causal Pathway Extraction from Web-Board Documents |
| description |
This research aim is to extract causal pathways, particularly disease causal pathways, through cause-effect relation (CErel) extraction from web-board documents. The causal pathways benefit people with a comprehensible representation approach to disease complication. A causative/effect-concept expression is based on a verb phrase of an elementary discourse unit (EDU) or a simple sentence. The research has three main problems; how to determine CErel on an EDU-concept pair containing both causative and effect concepts in one EDU, how to extract causal pathways from EDU-concept pairs having CErel and how to indicate and represent implicit effect/causative-concept EDUs as implicit mediators with comprehension on extracted causal pathways. Therefore, we apply EDU’s word co-occurrence concept (wrdCoc) as an EDU-concept and the self-Cartesian product of a wrdCoc set from the documents for extracting wrdCoc pairs having CErel into a wrdCoc-pair set from the documents after learning CErel on wrdCoc pairs by supervised-machine learning. The wrdCoc-pair set is used for extracting the causal pathways by wrdCoc-pair matching through the documents. We then propose transitive closure and a dynamic template to indicate and represent the implicit mediators with the explicit ones. In contrast to previous works, the proposed approach enables causal-pathway extraction with high accuracy from the documents. |
| format |
article |
| author |
Chaveevan Pechsiri Rapepun Piriyakul |
| author_facet |
Chaveevan Pechsiri Rapepun Piriyakul |
| author_sort |
Chaveevan Pechsiri |
| title |
Causal Pathway Extraction from Web-Board Documents |
| title_short |
Causal Pathway Extraction from Web-Board Documents |
| title_full |
Causal Pathway Extraction from Web-Board Documents |
| title_fullStr |
Causal Pathway Extraction from Web-Board Documents |
| title_full_unstemmed |
Causal Pathway Extraction from Web-Board Documents |
| title_sort |
causal pathway extraction from web-board documents |
| publisher |
MDPI AG |
| publishDate |
2021 |
| url |
https://doaj.org/article/9d85ae9a915a41d680dbfdf974c53dcd |
| work_keys_str_mv |
AT chaveevanpechsiri causalpathwayextractionfromwebboarddocuments AT rapepunpiriyakul causalpathwayextractionfromwebboarddocuments |
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1718435381350760448 |