NEUROCOMPUTING 2011 - NEUROCOMPUTING Special Issue on Learning from Social Media Network

Recent years have witnessed the popularity of web 2.0 content. Examples include Flickr, YouTube, Facebook, MySpace, etc. The proliferation of such applications on social web and social networks have produced a new type of multimedia content, termed as “social media” here as it is created by people using highly accessible and scalable publishing technologies for sharing via the web. The intrinsic attribute of social media is to facilitate interactive information sharing, interoperability and collaboration on the internet. By virtue of that, web images, videos and audios are generally accompanied by user-contributed contextual information such as, tag, category, title, metadata, comments, and viewer ratings, etc. Massive emerging social media data offer new opportunities for resolving the long-standing challenges such as how can we build video indexing and search benefit from the shared videos and other metadata? How can we deal with the large scale web videos by leveraging the video content and the user contributed information? Furthermore, this new media also introduces many challenging and new research problems and many exciting real-world applications (e.g. social image search, social group recommendation, etc.).
This special issue seeks for original contribution of works which address the challenges from learning based social media mining. The list of possible topics includes, but not limited to:

o Learning based social context analysis

o Understanding social media content using learning techniques

o Large scale image, video and audio classification (using social contextual cues)

o Learning to recommend (image, video and audio recommendation in social networks)

o Intelligent near-duplicate and copy detection

o Learn to advertise at online social media

o Learn to tackle privacy and security issues in social media (e.g. media watermarking)

o Learning to rank in media retrieval

o Learning based organization, indexing and navigation of multimedia content

o Interactive/collaborative image, video and audio search

Submission Guideline
Authors should prepare their manuscript (6-15 pages in the Neurocomputing publishing format) according to the Guide for Authors available from the online submission page of the Neurocomputing at http://ees.elsevier.com/neucom/. All the papers will be peer-reviewed following the Neurocomputing reviewing procedures.

Notes: when submitting your manuscript, at the step of “Selecting an Article Type is Required for Submission”, please indicate: “Special Issue: Learning from Social Media Network (LearningfromSMN)”.

Important Dates:
? Manuscript submission: 1 Nov. 2010
? First notification: 1 Feb. 2011
? Revised version: 1 Apr. 2011
? Notification: 1 Jun. 2011
? Final manuscript due: 1 Jul. 2011
? Anticipated publication: Autumn 2011

Guest Editors:
Richang Hong National University of Singapore hongrc-AT-comp.nus.edu.sg
Ling Shao University of Sheffield, UK ling.shao-AT-sheffield.ac.uk