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https://rda.sliit.lk/handle/123456789/1605
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DC Field | Value | Language |
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dc.contributor.author | Kulasinghe, S.A.S.A. | - |
dc.contributor.author | Jayasinghe, A. | - |
dc.contributor.author | Rathnayaka, R.M.A. | - |
dc.contributor.author | Karunarathne, P.B.M.M.D. | - |
dc.contributor.author | Silva, P.D.S. | - |
dc.contributor.author | Anuradha Jayakodi, J.A.D.C. | - |
dc.date.accessioned | 2022-03-14T07:25:28Z | - |
dc.date.available | 2022-03-14T07:25:28Z | - |
dc.date.issued | 2019-12-05 | - |
dc.identifier.isbn | 978-1-7281-4170-1/19 | - |
dc.identifier.uri | http://rda.sliit.lk/handle/123456789/1605 | - |
dc.description | Date of Conference: 5-7 Dec. 2019 Date Added to IEEE Xplore: 29 May 2020 | en_US |
dc.description.abstract | Suicide is a major issue in the world. The number one reason for suicide is untreated depression. That is why it was decided to focus on depression symptoms more and identify them in order to prevent suicidal attempts. To cure depression, the best way is to talk about their feelings with someone they trusted and release their pain inside of them. Because of that this system has a Chat-bot for the user to interact with. Chat-bot will gather information about the users feelings through text and voice analysis. Also by analyzing their Facebook statuses and recent web history, the application gather more information about their mental state so that the system take more accurate conclusions. After analyzing all the information from each component the back brain will decide on how the chat-bot should act on the user. At the end, the product was able to give more than 75% accurate results for each component. | en_US |
dc.language.iso | en | en_US |
dc.publisher | 2019 1st International Conference on Advancements in Computing (ICAC), SLIIT | en_US |
dc.relation.ispartofseries | Vol.1; | - |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Depression | en_US |
dc.subject | Suicide | en_US |
dc.subject | NLP | en_US |
dc.subject | Mobile Application | en_US |
dc.subject | Chat Bot | en_US |
dc.subject | Voice Analysis | en_US |
dc.subject | Sentimental Analysis | en_US |
dc.title | AI Based Depression and Suicide Prevention System | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/ICAC49085.2019.9103411 | en_US |
Appears in Collections: | 1st International Conference on Advancements in Computing (ICAC) | 2019 Department of Computer Systems Engineering-Scopes |
Files in This Item:
File | Description | Size | Format | |
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AI_Based_Depression_and_Suicide_Prevention_System.pdf Until 2050-12-31 | 400.44 kB | Adobe PDF | View/Open Request a copy |
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