Multimedia Data Mining and Analytics Disruptive Innovation /

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 des...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Baughman, Aaron K. (Editor ), Gao, Jiang (Editor ), Pan, Jia-Yu (Editor ), Petrushin, Valery A. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Temas:
Multimedia systems.
Data mining.
Computer vision.
Signal processing.
Technological innovations.
Artificial intelligence.
Multimedia Information Systems.
Data Mining and Knowledge Discovery.
Computer Vision.
Signal, Speech and Image Processing .
Innovation and Technology Management.
Artificial Intelligence.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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