| Document Date: 2011-11-19 02:38:44
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City New York City / Static / / Company 3M / Yahoo! / / Country United States / / Currency USD / / / Event Product Issues / Product Recall / / Facility Spain University of British Columbia Vancouver / S. Lakshmanan University of British Columbia Vancouver / / IndustryTerm induction algorithms / Web Applications / distributed learning algorithm / large networks / resistive networks / web-based social networks / data mining perspective / real-world social network / basic greedy algorithm / real social network / evaluation algorithm / online communities / greedy algorithm / Internet Technol / water bottle refilling network / greedy approximation algorithm / social networks / real social networks / social network / viral marketing applications / flickr social network / online social network / learning algorithm / online community / learning algorithms / / Organization Harvard / African Union / Spain University / University of British Columbia / / Person Threshold Model / Models As / / Position lazy-forward / General / Data Mining General / model for social networks / / Product Archos TV+ Portable Video Player (PVP) / MODELS / iPhone / values / Bernoulli / / ProvinceOrState British Columbia / New York / Connecticut / Nova Scotia / / PublishedMedium Machine Learning / Journal of Consumer Research / Harvard Business Review / / Technology 6.1 Algorithm / training algorithms / Av / greedy approximation algorithm / comparing induction algorithms / P2P / 247 6.3 Algorithm / testing algorithms / machine learning / viral marketing / basic greedy algorithm / EM algorithm / learning algorithm / distributed learning algorithm / evaluation algorithm / greedy algorithm / learning algorithms / Data Mining / / URL http /
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Learning Influence Probabilities In Social Networks Amit Goyal Francesco Bonchi Laks V. S. Lakshmanan