-------- Original-Nachricht -------- Betreff: [TCCC-ANNOUNCE] [Tccc] CFP: The 1st Mobile Sensing, Mining and Visualization for Human Behavior Inference Workshop, co-located with PAKDD 2014 Datum: Mon, 11 Nov 2013 16:02:04 +0800 Von: Fang-Jing Wu uklittlemoon@GMAIL.COM Antwort an: Fang-Jing Wu uklittlemoon@GMAIL.COM An: tccc-announce@COMSOC.ORG
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------------------------------------------------------------------------------------------------------------------- The 1st Mobile Sensing, Mining and Visualization for Human Behavior Inference Workshop, co-located with PAKDD 2014 -------------------------------------------------------------------------------------------------------------------
Call for Papers for the 1st Mobile Sensing, Mining and Visualization for Human Behavior Inference Workshop co-located with PAKDD 2014: The 18th Pacific-Asia Conference on Knowledge Discovery and Data (PAKDD 2014)
Organizers: Edward Y. Chang, HTC Corporation Fang-Jing Wu, Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR) Zhenhui Jessie Li, Pennsylvania State University
Venue & Dates: May 13, 2014, Tainan, Taiwan
Conference Website: http://hscc.cs.nctu.edu.tw/~fangjing/index.html
Introduction
The massive data streams and diverse modalities of digital information sources being captured at an incredible rate have enriched the confluence of ubiquitous computing, networking technologies, wireless sensor networks (WSNs), data mining, machine learning, and data visualization and also boosted many promising applications in environmental sensing, urban mobility, transportation, emergency response, social networks, healthcare, security, and IT infrastructure. However, the captured big data is usually sparsely collected, noisy, incomplete, and untrustworthy. Moreover, the sheer volume of sensor data, as well as its streaming and distributed nature, raises many technical challenges of mobile sensing, data mining, data visualization, and real-world applications. Government organizations, commercial enterprise, and individuals rely on different technologies form conventional wireless sensor platforms to smartphones to collect big sensing data, extract knowledge from the big data, and visualize big data from several perspectives so as to develop the expected applications in pervasive environments. Several successful applications attract not only the research efforts but also the industry investments for big data science.
As the big data science involved in developing applications for these classes of problems lies at the intersection of several diverse disciplines, the workshop aims at several important research topics, including (1) data sensing : how to collect multi-dimensional and high-quality data effectively, how to collect data without compromising personal privacy, and how to design incentive sensing models which may incorporate participatory sensing, crowdsourcing, cooperative and opportunistic sensing technologies for Novel Applications; (2) data mining : how current data mining, machine learning and knowledge discovery methods can be extended to mining solutions for dealing with real-world problems, how to infer human intentions, recognize activities and extract knowledge from unstructured data, and how to design distributed, parallel, and scalable mining algorithms to handle large, multi-modal, heterogeneous and distributed streams of data; and (3) data visualization : how to visualize heterogeneous streaming data in a real-time way, how to represent data in a more intuitive way, and how to abstract key information to visualize the relationship between data.
The 1st workshop on Mobile Sensing, Mining and Visualization for Human Behavior Inference will serve as a forum for researchers and technologists to discuss the state-of-the-art, present their contributions, and set future directions in big data science. This workshop encourages authors to develop real-world applications and evaluate their methodologies using the real big datasets and investigate challenging problems based on large-scale deployment in the real world. We plan to invite a keynote speaker who has pioneer contributions in several areas including indoor positioning, big data mining, social networking and search integration, and Web search (spam fighting) to give a talk about the current trend and the future development of big data science. The topics of interest related to this workshop include, but are not limited to:
- Mobile data collection models
- Participatory, opportunistic and collaborative sensing
- Mining large scale sensor data
- Activity recognition and subjective sensing for mobile and pervasive applications
- Data mining techniques for real-world pervasive computing applications
- Unsupervised methods for discovering interesting patterns
- Supervised machine learning methods for analyzing data in pervasive environments
- Streaming data visualization
- Visual search and recommendation
- Big data storytelling using visualization
- Scalable parallel visualization methods
- Test-beds and real-world deployments
- Big data sensing, mining, and visualization applications including cyber intelligence, cyber security, business intelligence, e-commerce, scientific data analysis, education, etc.
Submission Guidelines
The submitted paper should adhere to the double-blind review policy . All papers will be double-blind reviewed by the Program Committee on the basis of technical quality, relevance to the workshop scope, originality, significance, and clarity. All paper submissions will be handled electronically. Detailed instructions are provided on the workshop home page. Papers that do not comply with the Submission Guidelines will be rejected without review .
Each submitted paper should include an abstract up to 200 words and be not longer than 12 single-spaced pages with 10pt font size. Authors are strongly encouraged to use Springer LNCS/LNAI manuscript submission guidelines (available at http://www.springer.de/comp/lncs/authors.html ) for their initial submissions. All papers must be submitted electronically through the paper submission system in PDF format only.
The submitted papers must not be previously published anywhere, and must not be under consideration by any other conferences or journal during the workshop review process. Submitting a paper to the workshop means that if the paper is accepted, at least one author should attend the workshop to present the paper. For no-show authors, their affiliations will receive a notification. The program committee chairs are not allowed to submit papers to the conference for a fair review process.
We will reach Springer to include outstanding papers from PAKDD workshops in a LNCS/LNAI post Proceedings of PAKDD Workshops. The detailed information will be announced later. Thus, each workshop is expected to attract as many paper submission as possible in order to have high quality of workshop papers.
The paper submission website is available ( https://cmt.research.microsoft.com/HBI2014/).
Before submitting your paper, please carefully read and agree with the above submission policy and no-show policy.
Important Dates
Paper Submissions: Jan. 13, 2014 (midnight PST) Notification of Acceptance: Feb 12, 2014 Camera-Ready Due: Feb 28, 2014 Workshop Date: May 13, 2014
Contact
Please email inquiries concerning the 1st Mobile Sensing, Mining and Visualization for Human Behavior Inference Workshop to: Fang-Jing Wu: wufj AT i2r DOT a-star DOT edu DOT sg.
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