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Spam filtering / Computer-mediated communication / Email / Information technology management / Spam / Email spam / Mobile phone spam / Text messaging / Email filtering / Spamming / Internet / Computing


Exploiting Latent Content based Features for the Detection of Static SMS Spams Amir Karami University of Maryland Baltimore County Maryland, USA [removed]
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Document Date: 2014-11-13 13:58:31

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File Size: 312,98 KB

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City

Seattle / /

Company

SMS LDA / Content Features LDA. / Twitter / TPR FNR Precision / /

Country

United States / /

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Event

Product Issues / Product Recall / /

Facility

Static SMS Spams Amir Karami University of Maryland Baltimore County Maryland / ipgAAQ Lina Zhou University of Maryland Baltimore County Maryland / /

IndustryTerm

web spam detection / Web companion / online review / social networking sites / online consumer reviews / classification algorithms / social networks / nearest neighbor algorithm / supervised machine learning algorithms / communication media / /

NaturalFeature

Features Random Forest / Random Forest / /

Organization

ipgAAQ Lina Zhou University of Maryland Baltimore County Maryland / Static SMS Spams Amir Karami University of Maryland Baltimore County Maryland / International World Wide Web Conferences Steering Committee / /

Person

Andrew Y. Ng / Michael I. Jordan / /

Position

Author / /

Product

FMeasure AUC SC% BH% / /

PublishedMedium

Machine Learning / Linguistic Inquiry / /

Technology

40 classification algorithms / cellular telephone / SMS / Education Technology / SVM algorithms / nearest neighbor algorithm / classification algorithms / mobile phones / supervised machine learning algorithms / machine learning / 13 classification algorithms / /

URL

http /

SocialTag