Special Issue on Big Data Meets Multimedia Analytics
With the rapid development of computing and sensing technologies, such as the emergence of social networking websites and wearable devices, many new research opportunities and challenges for multimedia content analysis have arisen.
Many big data modeling methods, computing algorithms, and signal processing technologies have recently been successfully developed and applied to multimedia content analysis: for example, multi-view learning algorithms have been proposed for exploring the variety of multimedia content; sparse and manifold learning have been developed for high dimensional multimedia data representation; deep learning has produced promising results in large scale multimedia retrieval; and compressive sensing and new sampling schemes have been investigated for big data analytics.
Motivated by the inclination to collect a set of recent advances and results in these related topics, provide a platform for researchers to exchange their innovative ideas on big modeling and computing solutions for multimedia content analytics, and introduce interesting utilizations of modeling and computing algorithms for particular social/personal media applications, this special issue will target emergent big modeling and computing methods for multimedia signal processing and understanding (with a special focus on social media and personal data).
To summarize, this special issue welcomes a broad range of submissions on the development and use of artificial intelligence and computing techniques for multimedia analytics. We are especially interested in: 1) theoretical advances as well as algorithm developments in big data technology for specific social/personal media analytics problems; 2) reports of practical applications and system innovations in social/personal media analytics; and 3) novel datasets as test beds for new developments, preferably with implemented standard benchmarks. The following list suggests (but is not limited to) possible topics of interest:
Big Data Technology Specifically for Multimedia Analytics
Big Data Technology for Multimedia Annotation, Tagging and Classification
Big Data Technology for Multimedia Abstraction and Summarization
Big Data Technology for Multimedia Indexing and Retrieval
Big Data Technology and Computing for Social Media Analytics
Big Data Technology and Computing for Biological Data
Big Data Technology and Computing for Personal Data Mining
Modeling of Wearable Device Sensor Streams
Personal Data based Social Network Analysis and Web Mining
Cloud Computing for Social Intelligence and Personal Data
Deep Learning for Social Media Analytics
Deep Learning for Security in Social Media
Manuscript Submission: May 01, 2015 Initial Decision: August 01, 2015 R1 Version: October 01, 2015 Acceptance Notification: November 01, 2015 Final Manuscripts Due: November 15, 2015 Anticipated Publication: January 01, 2016