title: Mining human behavior for health promotion.
abstract: The monitoring of human lifestyles has gained much attention in the recent years. This work presents a novel approach to combine multiple context-awareness technologies for the automatic analysis of people's conduct in a comprehensive and holistic manner. Activity recognition, emotion recognition, location detection, and social analysis techniques are integrated with ontological mechanisms as part of a framework to identify human behavior. Key architectural components, methods and evidences are described in this paper to illustrate the interest of the proposed approach.
authors.forename: Oresti
authors.initials: O
authors.lastname: Banos
authors.forename: Jaehun
authors.initials: J
authors.lastname: Bang
authors.forename: Taeho
authors.initials: T
authors.lastname: Hur
authors.forename: Muhammad Hameed
authors.initials: MH
authors.lastname: Siddiqi
authors.forename: Huynh-The
authors.initials: HT
authors.lastname: Thien
authors.forename: Le-Ba
authors.initials: LB
authors.lastname: Vui
authors.forename: Wajahat Ali
authors.initials: WA
authors.lastname: Khan
authors.forename: Taqdir
authors.initials: T
authors.lastname: Ali
authors.forename: Claudia
authors.initials: C
authors.lastname: Villalonga
authors.forename: Sungyoung
authors.initials: S
authors.lastname: Lee
mesh_terms: D000293:Adolescent; D000328:Adult; D001519:Behavior; D057225:Data Mining / Q000379:methods*; D004644:Emotions; D006293:Health Promotion; D006801:Humans; D008019:Life Style; D009043:Motor Activity; D055815:Young Adult