Discovering word associations in news media via feature selection and sparse classification

MIR 2010 - Proceedings of the 2010 ACM SIGMM International Conference on Multimedia Information Retrieval

Volumn , Issue , 2010, Pages 211-220

  Gawalt, Brian ^a   Jia, Jinzhu ^a   Miratrix, Luke ^a   El Ghaoui, Laurent ^a   Yu, Bin ^a   Clavier, Sophie ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b SAN FRANCISCO STATE UNIVERSITY   (United States)

Author keywords

Evaluation; Logistic Regression; News Media; Regularization; Sparsity; Text Classification

Indexed keywords

CLASSIFICATION ALGORITHM; CLASSIFICATION PERFORMANCE; CLASSIFICATION TECHNIQUE; FEATURE SELECTION; HUMAN ASSESSMENT; HUMAN READERS; HUMAN SUBJECTS; IMAGING SCHEMES; LOGISTIC REGRESSION MODELS; LOGISTIC REGRESSIONS; NEW YORK TIME; NEWS ARTICLES; NEWS MEDIA; NUMBER AND SIZE; PREDICTIVE PERFORMANCE; QUERY WORDS; SPARSE CLASSIFICATION; SPARSE CLASSIFIERS; SPARSITY CONSTRAINTS; TEXT CLASSIFICATION; WEIGHT VECTOR; WORD ASSOCIATION; WORD LISTS;

ALGORITHMS; FEATURE EXTRACTION; FORECASTING; INFORMATION RETRIEVAL; LABELS; LOGISTICS; REGRESSION ANALYSIS; TEXT PROCESSING;

INFORMATION RETRIEVAL SYSTEMS;

EID: 77952390532     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1743384.1743421     Document Type: Conference Paper

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