Personalized Recommendation System for Efficient Integrated Cognitive Rehabilitation Training Based on Bigdata
| Autor: | Jeong Joon Kim, Sung-Taek Chung, Hyeok-Min Lee, Yong-Jun Kim, Sang-Ho Lee |
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| Rok vydání: | 2018 |
| Předmět: |
Multimedia
business.industry Process (engineering) Computer science Big data Cognition 02 engineering and technology Recommender system computer.software_genre 030227 psychiatry Visualization 03 medical and health sciences 0302 clinical medicine 0202 electrical engineering electronic engineering information engineering Unsupervised learning 020201 artificial intelligence & image processing Cognitive rehabilitation therapy business computer |
| Zdroj: | HCI International 2018 – Posters' Extended Abstracts ISBN: 9783319922782 HCI (29) |
| Popis: | In this study, a personalized recommendation system for efficient integrated cognitive rehabilitation training based on bigdata was developed. The system consists of 5 main phases (collection, storage, processing, analyzing, visualization). First, in the pre-processing process before the collection phase, resulting scores from multiple cognitive rehabilitation contents and patients’ personal information are saved in database. In the collection/storage phases, the patient information saved in the database is saved in bigdata platform. In the processing phase, the data are processed/refined in a necessary form to be utilized in the analysis and statistical processing program, R. Lastly, in the analysis/visualization phases, personalized contents of integrated cognitive rehabilitation training are recommended to patients using the K-Means method of the unsupervised learning algorithms and spiral model through patients’ personal information, MMSE results, cognitive rehabilitation contents results based on the processed/refined data. Patients can utilize the personalized recommendation system for integrated cognitive rehabilitation training based on bigdata to implement cognitive function evaluation and personalized training at home. |
| Databáze: | OpenAIRE |
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