An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages

Journal of Biomedical Informatics

Volumn 49, Issue , 2014, Pages 255-268

  Tuarob, Suppawong ^a   Tucker, Conrad S ^a,b   Salathe, Marcel ^b   Ram, Nilam ^b  

^a The Pennsylvania State University   (United States)

^b PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Classification; Machine learning; Social media

Indexed keywords

ARTIFICIAL INTELLIGENCE; EXPERIMENTS; HEALTH; INFORMATION RETRIEVAL SYSTEMS; LEARNING SYSTEMS; MATHEMATICAL MODELS; MEDICAL APPLICATIONS; PROBLEM ORIENTED LANGUAGES; SOCIAL NETWORKING (ONLINE); TEXT PROCESSING; VIRTUAL REALITY;

BIOMEDICAL APPLICATIONS; CLASSIFICATION METHODOLOGIES; DOCUMENT CLASSIFICATION; LARGE SCALE EXPERIMENTS; MACHINE LEARNING TECHNIQUES; SMALL-SCALE EXPERIMENT; SOCIAL MEDIA; WELL-ESTABLISHED TECHNIQUES;

CLASSIFICATION (OF INFORMATION);

ARTICLE; CLASSIFICATION; EVALUATION STUDY; EXPERIMENTAL MODEL; GRAMMAR; HEALTH; HEALTH EDUCATION; HUMAN; INTERNET; LANGUAGE; MACHINE LEARNING; METHODOLOGY; NORMAL HUMAN; PRIORITY JOURNAL; RANDOM SAMPLE; SOCIAL MEDIA; SOCIAL NETWORK; TEXT MESSAGING; ALGORITHM; ARTIFICIAL INTELLIGENCE; INFORMATION SERVICE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HEALTH EDUCATION; INFORMATION SERVICES; SOCIAL MEDIA;

EID: 84902539789     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2014.03.005     Document Type: Article

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