Multimedia data mining and analytics : disruptive innovation /
edited by Aaron K. Baughman, Jiang Gao, Jia-Yu Pan, Valery A. Petrushin.
- xiv, 454 páginas : 188 ilustraciones, 153 ilustraciones en color.
Springer eBooks
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.