| Title |
Analysis of Local Assembly Decision-making Process Using Facet LSTM Model |
| ID_Doc |
79240 |
| Authors |
Lee, T; Jeong, H; Kim, NR |
| Title |
Analysis of Local Assembly Decision-making Process Using Facet LSTM Model |
| Year |
2019 |
| Published |
|
| DOI |
10.1109/CSCI49370.2019.00287 |
| Abstract |
The objective of the study is to facilitate understanding of lengthy and complicated public discussioiis through a review of the meeting minutes from a local assembly and to derive from them distilled information usilig a big data machine learniiig model. To this end, we take the meeting minutes of the 7th basic assembly of Jin-gu Council in Busan and analyse three attributes: purpose of remark, presence of disagreement, and cause of coiiflict, as maiiifested throughout the discussion process through to the final decision making. |
| Author Keywords |
Local Assembly Decision-making; auto-classification; document classification; Facet Analysis; policy issue |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000569996300280 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
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