This unique compendium focuses on the acquisition and analysis of social media data. The approaches concern both the data-intensive characteristics and graphical structures of social media. The book addresses the critical problems in social media analysis, which representatively cover its lifecycle.

The must-have volume is an excellent reference text for professionals, researchers, academics and graduate students in AI and databases.

Contents: IntroductionAdaptive and Parallel Acquisition of Social Media Data from Online Big GraphsA Bayesian Network-Based Approach for Incremental Learning of Uncertain KnowledgeDiscovering User Similarities in social Behavioral Interactions Based on Bayesian NetworkAssociative Categorization of Frequent Patterns in Social Media Based on Markov NetworkMarkov Network Based Latent Link Discovery and Community Detection in Social Behavioral InteractionsProbabilistic Inferences of Latent Entity Associations in Textual Web ContentsContainment of Competitive Influence Spread on Social NetworksLocating Sources in Online Social Networks via Random Walk
Readership: Professionals, researchers, academics and graduate students in AI and databases.Social Media;Data Acquisition;Community Detection;Influence Propagation;Bayesian Network;Probabilistic Inference00

Hao Wu

Книги