Mining that involves finding representative knowledge in data is an essential step of intelligent data application. Traditionally, mining research has concerned itself with achieving completeness efficiently for homogeneous data. However, nowadays, easy data collection in a variety of research areas, including social networks, bioinformatics, mobile sensing, healthcare, security, etc., has led to a massive amount of diverse and heterogeneous data—the so-called multimedia data. As a result, there is an increasing demand for developing better methods for extracting knowledge from multimedia data and more practical intelligent applications based on the extracted knowledge.
There are several important aspects to mining knowledge from multimedia data. (1) multimedia data collection: how to collect meaningful and high-quality multimedia data effectively, without compromising personal privacy in different research domains; (2) multimedia mining: how to design appropriate algorithms for dealing with multimedia data sets that are beyond the ability of commonly used software tools to capture, curate, manage, and process within a tolerable elapsed time; (3) multimedia mining pattern visualization: how to present mining results in a more intuitive way, and how to abstract key information to visualize the relationship between multimedia data; and (4) practical application: how multimedia mining algorithms apply to the real-world.
The 1st International Workshop on Mining and Application of Multimedia (MAM) will serve as a forum for researchers and technologists to discuss the state-of-the-art, present their contributions, and set future directions in multimedia mining and applications. This workshop encourages authors to develop multimedia applications and evaluate their methodologies using real multimedia data and investigate challenging problems in the real world. We plan to invite a keynote speaker who has pioneer contributions in several related areas, including mining in social networking, bioinformatics, healthcare, and mobile sensing, etc., to give a talk about the current trend and the future development of multimedia. The topics of interest related to this workshop include, but are not limited to:
- Multimedia Collection
- Multimedia Cleaning
- Multimedia Visualization
- Mining Techniques on Multimedia
- Association Rules
- Sequential Patterns
- Structural Analysis
- Time Series Analysis
- Social Network
- Recommendation System
- Sensor Network
Workshop Paper Submission: September 12, 2017
Acceptance Notification: September 20, 2017
Camera-Ready: September 29, 2017
All submissions must be original work not under review by any other workshop, conference, or journal. The workshop will accept papers describing completed work as well as work-in- progress. Workshop papers will be included in the main conference proceedings and indexed into the IEEE Xplore Digital Library.
Manuscripts must be written in English and follow the instructions in the Manuscript Formatting and Templates page as the same as the main symposium requirements here. Please complete your submission to MAM2017 via EasyChair (https://easychair.org/conferences/?conf=mam2017).
Jiannong Cao, Hong Kong Polytechnic University, Hong Kong
Keith Chan, Hong Kong Polytechnic University, Hong Kong
Meng-Fen Chiang, Singapore Management University, Singapore
Kun-Ta Chuang, National Cheng Kung University, Taiwan
Xiaohua Tony Hu, Drexel University, USA
Joshua Zhexue Huang, Shenzhen University, China
Yan Huang, University of North Texas, USA
Wei-Shinn Ku, Auburn University, USA
Suh-Yin Lee, National Chiao Tung University, Taiwan
Wang-Chien Lee, The Pennsylvania State University, USA
Yan Liu, Hong Kong Polytechnic University, Hong Kong
Dai Bing Tian, Singapore Management University, Singapore
Vincent S. Tseng, National Chiao Tung University, Taiwan
Xing Xie, Microsoft Research Asia, China
Philip S. Yu, University of Illinois at Chicago, USA
Xiang Zhang, Case Western Reserve University, USA
Yi-Cheng Chen, National Central University, Taiwan
Bio: Yi-Cheng Chen received his Ph.D degree in the Department of Computer Science at National Chiao Tung University, Taiwan, in 2012. Currently, he is an assistant professor in the Department of Information Management at National Central University, Taiwan. He has been active in international academic activities, as conference organizer, journal editor/reviewer. His research interests include: data mining, social network analysis, cloud computing and bioinformatics.
Chih-Hua Tai, National Taipei University, Taiwan
Bio: Chih-Hua Tai received her Ph.D. degree from Department of Electrical Engineering, National Taiwan University (NTU), Taipei, Taiwan. She is currently an assistant professor in Department of Computer Science and Information Engineering, National Taipei University, New Taipei City, Taiwan. She has been active in international academic activities, as conference organizer, journal editor/reviewer. Her research interests include privacy-preserving data mining, healthcare data mining, and social media computing and marketing. She received the best paper award of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2015).