| 紀錄類型: |
書目-電子資源
: Monograph/item
|
| 杜威分類號: |
302.23/1 |
| 書名/作者: |
Probabilistic approaches for social media analysis : data, community and influence // Kun Yue ... [et al.]. |
| 其他作者: |
Yue, Kun. |
| 出版者: |
Singapore : : World Scientific,, c2020. |
| 面頁冊數: |
1 online resource (292 p.) |
| 標題: |
Social media - Data processing. |
| 標題: |
Text processing (Computer science) |
| 標題: |
Quantitative research - Statistical methods. |
| 標題: |
Machine learning. |
| 標題: |
Content analysis (Communication) - Data processing. |
| ISBN: |
9789811207389 |
| ISBN: |
9811207380 |
| 書目註: |
Includes bibliographical references and index. |
| 內容註: |
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. |
| 摘要、提要註: |
"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. |
| 電子資源: |
https://www.worldscientific.com/worldscibooks/10.1142/11476#t=toc |