Discriminating between empirical studies and nonempirical works using automated text classification

Research Synthesis Methods

Volumn 9, Issue 4, 2018, Pages 587-601

  Langlois, Alexis ^a   Nie, Jian Yun ^a   Thomas, James ^b   Hong, Quan Nha ^c   Pluye, Pierre ^c  

^a UNIVERSITÉ DE MONTRÉAL   (Canada)

^b UNIVERSITY OF LONDON   (United Kingdom)

^c MCGILL UNIVERSITY   (Canada)

Author keywords

automated text classification; decision tree; health care; research method; support vector machine; systematic review

Indexed keywords

ALGORITHM; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; BIBLIOGRAPHIC DATABASE; DATA MINING; DOCUMENTATION; HUMAN; INFORMATION RETRIEVAL; METHODOLOGY; PROCEDURES; SEARCH ENGINE; SENSITIVITY AND SPECIFICITY; STANDARD; STANDARDS; STATISTICAL MODEL; SUPPORT VECTOR MACHINE;

ALGORITHMS; BAYES THEOREM; DATA MINING; DATABASES, BIBLIOGRAPHIC; HUMANS; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REFERENCE STANDARDS; RESEARCH DESIGN; SEARCH ENGINE; SENSITIVITY AND SPECIFICITY; SUBJECT HEADINGS; SUPPORT VECTOR MACHINE; SYSTEMATIC REVIEWS AS TOPIC;

EID: 85057968335     PISSN: None     EISSN: 17592887     Source Type: Journal    
DOI: 10.1002/jrsm.1317     Document Type: Conference Paper

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