Submission Deadline: 15 December 2017
IEEE Access invites manuscript submissions in the area of Sequential Data Modeling and Its Emerging Applications.
With the tremendous advance of technologies in data collection and storage, sequential data is becoming more and more ubiquitous in a wide spectrum of application scenarios. There are various embodiments of sequential data such as time series/video frames and event data, where the former is synchronous over time and the latter is often generated in an asynchronous fashion. It bears important practical utility for learning and understanding the dynamic behavior as well as the causality relationships across sequences, and it also calls for robust models to handle with noisy and incomplete sequence data in real-world settings.
The objective of this Special Section in IEEE Access is to bring together the state-of-the-art research contributions that address key aspects of sequential data modeling and their novel applications, such as sequence learning for clinical trials in healthcare, failure tickets in device maintenance, transactions in e-commerce, which will help identify the fundamental methodology and key technology for cross-discipline research and applications. All submitted articles will be peer-reviewed and selected on the basis of their quality and relevance to the theme of this Special Section.
The topics of interest include, but are not limited to:
We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.
Associate Editor: Junchi Yan, IBM Research, China
Relevant IEEE Access Special Sections:
IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland
Paper submission: Contact Associate Editor and submit manuscript to:
For inquiries regarding this Special Section, please contact: firstname.lastname@example.org