Nugroho, Robertus Setiawan Aji Personal Health Mention Identification from Social Media. Unika. (Unpublished)
![[img]](http://repository.unika.ac.id/style/images/fileicons/text.png) |
Text
penelitian_health_mention.pdf Restricted to Registered users only Download (2MB) |
Abstract
The sudden increase of COVID19 infections in June 2021 due to the new variant has put new challenges for the tracing and tracking of the infected people. Our previous works on the development of the personal health mention (PHM) algorithm has shown a consistent performance on identifying health symptoms from social media posts. However, to get better results, we need to investigate the dynamic of the social media. In this research we propose the real-time implementation of our PHM algorithm. We extend the algorithm to involve the dynamicity of the social media content and improve the accuracy using more complex translation picking approach on building the data training. This research implements the developed algorithm for online and continuous personal health mention monitoring.
| Item Type: | Other |
|---|---|
| Subjects: | 000 Computer Science, Information and General Works 000 Computer Science, Information and General Works > 004 Data processing & computer science |
| Divisions: | Faculty of Computer Science > Department of Informatics Engineering |
| Depositing User: | Mr R. Setiawan Aji Nugroho |
| Date Deposited: | 30 Aug 2022 21:09 |
| Last Modified: | 30 Aug 2022 21:09 |
| URI: | http://repository.unika.ac.id/id/eprint/29113 |
Actions (login required)
 |
View Item |
