Neural Networks / Twitter / Youtube / Facebook / Army Research Laboratory / Learning Systems / Positive Networks / IBM / /
Country
China / /
Currency
USD / / /
Facility
University of Illinois / Army Research Laboratory / Arizona State University Beckman Institute / /
IndustryTerm
realworld social media datasets / supervised link prediction algorithms / basic algorithms / unsupervised link prediction algorithms / offthe-shelf opinion mining / given unsigned network / weighted signed network / data mining / breadth-first search / recommender systems / social media applications / signed social network / heterogenous networks / basic algorithm / sparse network / target network / negative network / positive network / source network / social media / social media sites / mature signed network / large-scale online social network data / unsupervised algorithms / product review site / noise-tolerant algorithms / signed social networks / large-scale social networks / social media activities6 / real-world social networks / Web search / Social networks / technology news platform / given positive network / social network / social-media-brand-followers-hunting-for-deals / social media services / real-world social media datasets / /
Organization
Cambridge university / office of Naval Research / U.S. Army Research Office / U.S. Government / International World Wide Web Conferences Steering Committee / Arizona State University Beckman Institute / University of Illinois / /
Person
Huan Liu / /
Position
Prime Minister / Information filtering General / /
ProvinceOrState
Illinois / /
PublishedMedium
Machine Learning / Psychological Review / /
Technology
noise-tolerant algorithms / machine learning / knowledge management / artificial intelligence / supervised link prediction algorithms / data mining / unsupervised link prediction algorithms / basic algorithm / /
Negative Link Prediction in Social Media Jiliang Tang‡ , Shiyu Chang] , Charu Aggarwal† and Huan Liu‡ ‡ ]