PHP | Data mining | Majour Project | 2023-11-10 02:47:17
Psychological stress is threatening people's health. It is non-trivial to detect stress timely for proactive care. With the popularity of social media, people are used to sharing their daily activities and interacting with friends on social media platforms, making it feasible to leverage online social network data for stress detection. In this paper, we find that users stress state is closely related to that of his/her friends in social media, and we employ a large-scale dataset from real-world social platforms to systematically study the correlation of users' stress states and social interactions. We first define a set of stress-related textual, visual, and social attributes from various aspects, and then propose a novel hybrid model - a factor graph model combined with Convolutional Neural Network to leverage tweet content and social interaction information for stress detection.
BLOOD BANK APPLICATION
Real-time |
PHP | Majour Project |
2023-11-09 00:38:52
Feed Waste management system
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PHP | Majour Project |
2023-11-10 02:18:33
ONLINE FOOD ORDERING SYSTEM
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PHP | Majour Project |
2023-11-10 02:21:07
Online Secure Health Care System
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PHP | Majour Project |
2023-11-10 02:44:43
ONLINE WEB BASED CHAT
Real-time |
PHP | Majour Project |
2023-11-10 02:23:28