Probabilistic approaches for social media analysis data, community and influence / [electronic resource] :
Kun Yue ... [et al.].
- Singapore : World Scientific, 2020.
- 1 online resource (292 p.).
- East China Normal University scientific reports, vol. 11 2382-5715 ; .
- East China Normal University scientific reports ; vol. 11. .
Includes bibliographical references and index.
Introduction -- Adaptive and parallel acquisition of social media data from online big graphs -- A Bayesian network-based approach for incremental learning of uncertain knowledge -- Discovering user similarities in social behavioral interactions based on Bayesian network -- Associative categorization of frequent patterns in social media based on Markov network -- Markov network based latent link discovery and community detection in social behavioral interactions -- Probabilistic inferences of latent entity associations in textual web contents -- Containment of competitive influence spread on social networks -- Locating sources in online social networks via random walk.
"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"--Publisher's website.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat reader.
9789811207389 9811207380
Social media--Data processing.
Text processing (Computer science)
Quantitative research--Statistical methods.
Machine learning.
Content analysis (Communication)--Data processing.
Electronic books.
HM742 / .P679 2020
302.23/1
Includes bibliographical references and index.
Introduction -- Adaptive and parallel acquisition of social media data from online big graphs -- A Bayesian network-based approach for incremental learning of uncertain knowledge -- Discovering user similarities in social behavioral interactions based on Bayesian network -- Associative categorization of frequent patterns in social media based on Markov network -- Markov network based latent link discovery and community detection in social behavioral interactions -- Probabilistic inferences of latent entity associations in textual web contents -- Containment of competitive influence spread on social networks -- Locating sources in online social networks via random walk.
"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"--Publisher's website.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat reader.
9789811207389 9811207380
Social media--Data processing.
Text processing (Computer science)
Quantitative research--Statistical methods.
Machine learning.
Content analysis (Communication)--Data processing.
Electronic books.
HM742 / .P679 2020
302.23/1