Selecting discriminative features in social media data: An unsupervised approach

Neurocomputing

Volumn 205, Issue , 2016, Pages 463-471

  Hoseini, Elham ^a   Mansoori, Eghbal G ^a  

^a SHIRAZ UNIVERSITY   (Iran)

Author keywords

Graph partitioning; Link information; Social media; Unsupervised feature selection

Indexed keywords

ALGORITHMS; CLUSTERING ALGORITHMS; DATA HANDLING; DATA MINING; FEATURE EXTRACTION; ITERATIVE METHODS; SOCIAL SCIENCES COMPUTING;

DISCRIMINATIVE FEATURES; GRAPH PARTITIONING; HIGH DIMENSIONAL DATA; LINK INFORMATIONS; OBJECTIVE FUNCTIONS; SOCIAL MEDIA; UNSUPERVISED APPROACHES; UNSUPERVISED FEATURE SELECTION;

SOCIAL NETWORKING (ONLINE);

ARTICLE; CLASSIFICATION ALGORITHM; CONTROLLED STUDY; LAPLACIAN SCORE; LEARNING ALGORITHM; LINEAR SYSTEM; MEASUREMENT ACCURACY; MULTICLASS RELIEFF; NON NEGATIVE MATRIX FACTORIZATION; PRIORITY JOURNAL; SOCIAL NETWORK; SPECTRAL FEATURE SELECTION ALGORITHM; UNSUPERVISED FEATURE SELECTION FRAMEWORK FOR SOCIAL NETWORK DATA;

EID: 84969951768     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2016.03.078     Document Type: Article

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