Multimedia Data Mining and Analytics Disruptive Innovation /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Baughman, Aaron K. (Επιμελητής έκδοσης), Gao, Jiang (Επιμελητής έκδοσης), Pan, Jia-Yu (Επιμελητής έκδοσης), Petrushin, Valery A. (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2015.
• Θέματα: Computer science.; Management.; Industrial management.; Data mining.; Multimedia information systems.; Artificial intelligence.; Image processing.; Computer Science.; Multimedia Information Systems.; Data Mining and Knowledge Discovery.; Image Processing and Computer Vision.; Signal, Image and Speech Processing.; Innovation/Technology Management.; Artificial Intelligence (incl. Robotics).

 This authoritative text/reference provides fresh insights into the cutting edge of multimedia data mining, reflecting how the research focus has shifted towards networked social communities, mobile devices and sensors. Presenting a detailed exploration into the progression of the field, the book describes how the history of multimedia data processing can be viewed as a sequence of disruptive innovations. Across the chapters, the discussion covers the practical frameworks, libraries, and open source software that enable the development of ground-breaking research into practical applications. Topics and features: · Contains contributions from an international selection of pre-eminent authorities in the field · Reviews how disruptive innovations in mobile, social, cognitive, cloud and organic based computing impacts upon the development of multimedia data mining · Provides practical details on implementing the technology for solving real-world multimedia problems · Includes chapters devoted to privacy issues in multimedia social environments, and large-scale biometric data processing · Covers content and concept based multimedia search, and advanced algorithms for multimedia data representation, processing and visualization The illuminating viewpoints presented in this comprehensive volume will be of great interest to researchers and graduate students involved in machine learning and pattern recognition, as well as to professional multimedia analysts and software developers. 

 Part I: Introduction -- Disruptive Innovation: Large Scale Multimedia Data Mining -- Part II: Mobile and Social Multimedia Data Exploration -- Sentiment Analysis Using Social Multimedia -- Twitter as a Personalizable Information Service -- Mining Popular Routes from Social Media -- Social Interactions over Location-Aware Multimedia Systems -- In-house Multimedia Data Mining -- Content-based Privacy for Consumer-Produced Multimedia -- Part III: Biometric Multimedia Data Processing -- Large-scale Biometric Multimedia Processing -- Detection of Demographics and Identity in Spontaneous Speech and Writing -- Part IV: Multimedia Data Modeling, Search and Evaluation -- Evaluating Web Image Context Extraction -- Content Based Image Search for Clothing Recommendations in E-Commerce -- Video Retrieval based on Uncertain Concept Detection using Dempster-Shafer Theory -- Multimodal Fusion: Combining Visual and Textual Cues for Concept Detection in Video -- Mining Videos for Features that Drive Attention -- Exposing Image Tampering with the Same Quantization Matrix -- Part V: Algorithms for Multimedia Data Presentation, Processing and Visualization -- Fast Binary Embedding for High-Dimensional Data -- Fast Approximate K-Means via Cluster Closures -- Fast Neighborhood Graph Search using Cartesian Concatenation -- Listen to the Sound of Data.