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Human-Centered Social Media Analytics Softcover reprint of the original 1st ed. 2014 [Pehme köide]

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  • Formaat: Paperback / softback, 208 pages, kõrgus x laius: 235x155 mm, kaal: 3401 g, 51 Illustrations, color; 46 Illustrations, black and white; VIII, 208 p. 97 illus., 51 illus. in color., 1 Paperback / softback
  • Ilmumisaeg: 23-Aug-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319347098
  • ISBN-13: 9783319347097
Teised raamatud teemal:
Human-Centered Social Media Analytics Softcover reprint of the original 1st ed. 2014Suurem pilt
  • Formaat: Paperback / softback, 208 pages, kõrgus x laius: 235x155 mm, kaal: 3401 g, 51 Illustrations, color; 46 Illustrations, black and white; VIII, 208 p. 97 illus., 51 illus. in color., 1 Paperback / softback
  • Ilmumisaeg: 23-Aug-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319347098
  • ISBN-13: 9783319347097
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783319347097.html
Märksõnad:
This book provides a timely and unique survey of next-generation social computational methodologies. The text explains the fundamentals of this field, and describes state-of-the-art methods for inferring social status, relationships, preferences, intentions, personalities, needs, and lifestyles from human information in unconstrained visual data. Topics and features: includes perspectives from an international and interdisciplinary selection of pre-eminent authorities; presents balanced coverage of both detailed theoretical analysis and real-world applications; examines social relationships in human-centered media for the development of socially-aware video, location-based, and multimedia applications; reviews techniques for recognizing the social roles played by people in an event, and for classifying human-object interaction activities; discusses the prediction and recognition of human attributes via social media analytics, including social relationships, facial age and beauty,

and occupation.

Part I: Social Relationships in Human-Centered MediaBridging Human-Centered Social Media Content across Web DomainsSuman Deb Roy, Tao Mei, and Wenjun ZengLearning Social Relations from Videos: Features, Models and AnalyticsLei Ding and Alper YilmazCommunity Understanding in Location-Based Social NetworksYi-Liang Zhao, Qiang Cheng, Shuicheng Yan, Daqing Zhang, and Tat-Seng ChuaSocial Role Recognition for Human Event UnderstandingVignesh Ramanathan, Bangpeng Yao, and Li Fei-FeiIntegrating Randomization and Discrimination for Classifying Human-Object Interaction ActivitiesAditya Khosla, Bangpeng Yao, and Li Fei-FeiPart II: Human Attributes in Social Media AnalyticsRecognizing People in Social ContextGang Wang, Andrew Gallagher, Jiebo Luo, and David ForsythFemale Facial Beauty Attribute Recognition and EditingJinjun Wang, Yihong Gong, and Douglas GrayFacial Age Estimation: A Data Representation Perspective Xin GengIdentity and Kinship Relations in Group Pict

uresMing Shao, Siyu Xia, and Yun FuRecognizing Occupations through Probabilistic Models: A Social ViewMing Shao and Yun Fu

Arvustused

Human-Centered Social Media Analytics focuses on the novel social computational methodologies that are being developed to investigate social media data. Scholars, both new and established, should consider reading to gain an understanding of the questions they should pursue and the challenges they must overcome as they strive to advance big data and social media analytics research. (Pratyush Bharati, Interfaces, Vol. 47 (3), May-June, 2017)

Part I: Social Relationships in Human-Centered Media.- Bridging Human-Centered Social Media Content across Web Domains.- Learning Social Relations from Videos.- Community Understanding in Location-Based Social Networks.- Social Role Recognition for Human Event Understanding.- Integrating Randomization and Discrimination for Classifying Human-Object Interaction Activities.- Part II: Human Attributes in Social Media Analytics.- Recognizing People in Social Context.- Female Facial Beauty Attribute Recognition and Editing.- Facial Age Estimation.- Identity and Kinship Relations in Group Pictures.- Recognizing Occupations through Probabilistic Models.