Multimedia Data Mining and Analytics: Disruptive Innovation

This book 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. The work 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. Features: reviews how 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 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.

Table of Contents

Chapter Part I Introduction
Chapter 1 Disruptive Innovation: Large Scale Multimedia Data Mining

Part II Mobile and Social Multimedia Data Exploration
Chapter 2 Sentiment Analysis Using Social Multimedia
Chapter 3 Twitter as a Personalizable Information Service
Chapter 4 Mining Popular Routes from Social Media
Chapter 5 Social Interactions over Location-Aware Multimedia Systems
Chapter 6 In-house Multimedia Data Mining
Chapter 7 Content-Based Privacy for Consumer-Produced Multimedia

Part III Biometric Multimedia Data Processing
Chapter 8 Large-Scale Biometric Multimedia Processing
Chapter 9 Detection of Demographics and Identity in Spontaneous Speech and Writing

Part IV Multimedia Data Modeling, Search and Evaluation
Chapter 10 Evaluating Web Image Context Extraction
Chapter 11 Content Based Image Search for Clothing Recommendations in E-Commerce
Chapter 12 Video Retrieval Based on Uncertain Concept Detection Using Dempster–Shafer Theory
Chapter 13 Multimodal Fusion: Combining Visual and Textual Cues for Concept Detection in Video
Chapter 14 Mining Videos for Features that Drive Attention
Chapter 15 Exposing Image Tampering with the Same Quantization Matrix

Part V Algorithms for Multimedia Data Presentation, Processing and Visualization
Chapter 16 Fast Binary Embedding for High-Dimensional Data
Chapter 17 Fast Approximate K-Means via Cluster Closures
Chapter 18 Fast Neighborhood Graph Search Using Cartesian Concatenation
Chapter 19 Listen to the Sound of Data