Call for Papers
Today there are lots of heterogeneous and homogeneous media data from multiple
sources, such as news media websites, microblog, mobile phone, social networking
websites, and photo/video sharing websites. Integrated together these media data
represent different aspects of the real-world and help document the evolution of
the world. Consequently, it is impossible to correctly conceive and to appropriately
understand the world without exploiting the data available on these different sources
of rich multimedia content simultaneously and synergistically.
Cross-media analysis is a research area in the general field of multimedia content
analysis which focuses on the exploitation of the data with different modalities from
multiple sources simultaneously and synergistically to discover knowledge and
understand the world.
Specifically, we emphasize two essential elements in the study of cross-media
analysis that help differentiate cross-media analysis from the rest of the research in
multimedia content analysis or machine learning.
The first is the simultaneous co-existence of data from two or more different data
sources. This element indicates the concept of "cross", e.g., cross-modality, cross-
source, and cross cyberspace to reality. Cross-modality means that heterogeneous
features are obtained from the data in different modalities; cross-source means that
the data may be obtained across multiple sources (domains or collections); cross-
space means that the virtual world (i.e., cyberspace) and the real world (i.e., reality)
complement each other.
The second is the leverage of different types of data across multiple sources for
strengthening the knowledge discovery, for example, discovering the (latent)
correlation or synergy between the data with different modalities across multiple
sources, transferring the knowledge learned from one domain (e.g., a modality or a
space) to generate knowledge in another related domain, and generating a summary
with the data from multiple sources.
There two essential elements help promote cross-media analysis as a new, emerging,
and important research area in today's multimedia research. With the emphasis on
knowledge discovery, cross-media analysis is different from the traditional research
areas such as cross-lingual translation. On the other hand, with the general scenarios
of the leverage of different types of data across multiple sources for strengthening the
knowledge discovery, cross-media analysis addresses a broader series of problems
than the traditional research areas such as transfer learning. Overall, cross-media
analysis is beneficial for many applications in data mining, causal inference, machine
learning, multimedia, and public security.
Examples of the problems related to cross-media analysis include but are not limited to:
We welcome contributions from all the parties interested in cross-media analysis. We
shall have a peer review process to ensure the high quality of the papers to appear in
the special issue. At least three reviews shall be solicited before a paper is warranted
to publish in this special issue.
Zhongfei (Mark) Zhang
Computer Science Department, Watson School of Engineering and Applied Science
SUNY Binghamton
Binghamton, NY 13902-6000
USA
Yueting Zhuang
College of Computer Science
Zhejiang University,
Hangzhou, 310027 P.R. China
Ramesh Jain
Department of Computer Science
University of California, Irvine
Irvine, CA 92697-3425
USA
Jia-Yu (Tim) Pan
Mountain View, CA 94041
USA
7/15/2013: Deadline of the submissions
10/15/2013: Notifications to authors for the first round of reviews
12/1/2013: Deadline of the revised submissions
12/15/2013: Decisions made for all the accepted papers
2014: Publication of this special issue
Papers are submitted to the Journal's online submission system at:
http://www.editorialmanager.com/mmir/default.asp
which can also be accessed from the Journal's webpage at:
and click "Submit Online" button at the right panel of the Journal page.
You will then be asked to login to the online submission system using your registered user name and password. If you are new to the system, you need to first register to the system to get your user name and password by clicking the "REGISTER" button. After you have logged into the system, under the "New Submissions" panel, click the "Submit New Manuscript" link. Then you will see a pull-down menu of article types, and you will see the special track for this special issue: S.I.:Cross Media Analysis. By choosing this article type, you will be led to the online submission process for the special issue.