Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Fang, Ying-En | en_US |
dc.contributor.author | Tai, Chih-Hua | en_US |
dc.contributor.author | Chang, Yue-Shan | en_US |
dc.contributor.author | Fan, Chih-Tien | en_US |
dc.date.accessioned | 2017-04-21T06:48:53Z | - |
dc.date.available | 2017-04-21T06:48:53Z | - |
dc.date.issued | 2014 | en_US |
dc.identifier.isbn | 978-1-4799-3840-7 | en_US |
dc.identifier.issn | 1062-922X | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/134990 | - |
dc.description.abstract | With the advances of information technology, there are increasing researches aiming at assisting depression diagnosis and treatment. In most of them the user is necessarily actively joining the diagnosis and treatment program while he has perceived mental disorder himself. In order to early prevent the mental disorder, in this paper we propose an early warning mechanism that observes and mines user diary published on social network platform, and generates a score of getting mental disordered or depressed. If the score is large than a threshold, the system can notify the user and his friends on the social network to take care about the friend. We have conducted experiments to evaluate the proposed approach, and the results show that the proposed approach is effective. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Mental Disorder | en_US |
dc.subject | Depression diagnosis | en_US |
dc.subject | Social network | en_US |
dc.subject | Bayes methods | en_US |
dc.subject | Ontology | en_US |
dc.title | A Mental Disorder Early Warning Approach by Observing Depression Symptom in Social Diary | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | 2014 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC) | en_US |
dc.citation.spage | 2060 | en_US |
dc.citation.epage | 2065 | en_US |
dc.contributor.department | 資訊工程學系 | zh_TW |
dc.contributor.department | Department of Computer Science | en_US |
dc.identifier.wosnumber | WOS:000370963702030 | en_US |
dc.citation.woscount | 0 | en_US |
Appears in Collections: | Conferences Paper |