Context Mining based Mental Health Model for Lifecare Platform

Abstract

With the emergence of the 4th industrial revolution, IT convergence engineering based artificial intelligence and intelligent system has constantly been researched in today’s society. In particular, healthcare service based on IT-BT convergence helps to improve quality of people’s life and provide user-oriented healthcare contents actively. Currently, the healthcare industry has gradually changed its healthcare paradigm from conventional healthcare to mental diseases care and tries to solve the social problem with depression, one of mental disorders. This study proposes the context mining based mental health model for the lifecare platform. This study makes use of users’ profiles about depression and health weather index provided by Korea Meteorological Administration to classify and define semantic ontology based context information, and to develop the context mining model for depression index service. The proposed context mining based mental health model uses personalized context information so that it is possible to provide personalized depression index service, rather than unified healthcare service. Also, the proposed one uses user-based information for modeling so that it can provide guidelines for developing data model of depression. In addition, it is possible to provide accurate and specified service for users and efficient depression index service through customized service. The result of the proposed method shows that the context mining model not only promotes the theory and practical ability but also consolidates their understanding of web engineering models and concepts.