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Volumn 53, Issue 4, 2012, Pages 712-718

On developing robust models for favourability analysis: Model choice, feature sets and imbalanced data

Author keywords

Bayesian models; Favourability analysis; Imbalanced data; Machine learning; Sentiment analysis; Support vector machines

Indexed keywords

BAYESIAN MODEL; CLASSIFICATION PROCESS; DATA SETS; FAVOURABILITY ANALYSIS; FEATURE SETS; IMBALANCED DATA; INPUT DATAS; MACHINE-LEARNING; MODEL CHOICE; OPINION MINING; ROBUST MODELS; SENTIMENT ANALYSIS; TIME-PERIODS; TRAINING STRATEGY; UNDER-SAMPLING;

EID: 84865482239     PISSN: 01679236     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.dss.2012.05.028     Document Type: Conference Paper
Times cited : (69)

References (39)
  • 5
    • 0031334221 scopus 로고    scopus 로고
    • Selection of relevant features and examples in machine learning
    • A.L. Blum, and P. Langley Selection of relevant features and examples in machine learning Artificial Intelligence 97 1997 245 271
    • (1997) Artificial Intelligence , vol.97 , pp. 245-271
    • Blum, A.L.1    Langley, P.2
  • 9
    • 2942731012 scopus 로고    scopus 로고
    • An extensive empirical study of feature selection metrics for text classification
    • G. Forman An extensive empirical study of feature selection metrics for text classification The Journal of Machine Learning Research 3 2003 1289 1305
    • (2003) The Journal of Machine Learning Research , vol.3 , pp. 1289-1305
    • Forman, G.1
  • 15
    • 84957069814 scopus 로고    scopus 로고
    • Text categorization with support vector machines: Learning with many relevant features
    • T. Joachims Text categorization with support vector machines: learning with many relevant features C. Nédellec, C. Rouveirol, Machine Learning: ECML-98 Lecture Notes in Computer Science vol. 1398 1998 Springer Berlin / Heidelberg 137 142
    • (1998) Machine Learning: ECML-98 Lecture Notes in Computer Science , vol.1398 , pp. 137-142
    • Joachims, T.1
  • 16
    • 33646890004 scopus 로고    scopus 로고
    • The importance of neutral examples for learning sentiment
    • M. Koppel, and J. Schler The importance of neutral examples for learning sentiment Computational Intelligence 22 2006 100 109
    • (2006) Computational Intelligence , vol.22 , pp. 100-109
    • Koppel, M.1    Schler, J.2
  • 18
    • 0031998121 scopus 로고    scopus 로고
    • Machine learning for the detection of oil spills in satellite radar images
    • M. Kubat, R.C. Holte, and S. Matwin Machine learning for the detection of oil spills in satellite radar images Machine Learning 30 1998 195 215
    • (1998) Machine Learning , vol.30 , pp. 195-215
    • Kubat, M.1    Holte, R.C.2    Matwin, S.3
  • 20
    • 71649085616 scopus 로고    scopus 로고
    • Using text mining and sentiment analysis for online forums hotspot detection and forecast
    • N. Li, and D.D. Wu Using text mining and sentiment analysis for online forums hotspot detection and forecast Decision Support Systems 48 2010 354 368
    • (2010) Decision Support Systems , vol.48 , pp. 354-368
    • Li, N.1    Wu, D.D.2
  • 28
    • 62349089279 scopus 로고    scopus 로고
    • Sentiment analysis: A combined approach
    • R. Prabowo, and M. Thelwall Sentiment analysis: a combined approach Journal of Informetrics 3 2009 143 157
    • (2009) Journal of Informetrics , vol.3 , pp. 143-157
    • Prabowo, R.1    Thelwall, M.2
  • 31
    • 70350565063 scopus 로고    scopus 로고
    • On strategies for imbalanced text classification using SVM: A comparative study
    • A. Sun, E.-P. Ling, and Y. Lui On strategies for imbalanced text classification using SVM: a comparative study Decision Support Systems 48 2010 191 201
    • (2010) Decision Support Systems , vol.48 , pp. 191-201
    • Sun, A.1    Ling, E.-P.2    Lui, Y.3
  • 32
    • 84881506644 scopus 로고    scopus 로고
    • Aggregating opinions: Explorations into graphs and media content analysis
    • G. Tatzl, and C. Waldhauser Aggregating opinions: explorations into graphs and media content analysis TextGraphs-5 Workshop, ACL 2010 2010 93
    • (2010) TextGraphs-5 Workshop, ACL 2010 , pp. 93
    • Tatzl, G.1    Waldhauser, C.2
  • 33
    • 85136072040 scopus 로고    scopus 로고
    • Thumbs up or thumbs down?: Semantic orientation applied to unsupervised classification of reviews
    • Association for Computational Linguistics
    • P.D. Turney Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews Proceedings of the 40th Annual Meeting on Association for Computational Linguistics Association for Computational Linguistics 2002 417 424
    • (2002) Proceedings of the 40th Annual Meeting on Association for Computational Linguistics , pp. 417-424
    • Turney, P.D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.