[Call for Paper]

Workshop: Semantic Web-based R&D Trend Analysis on BigData

 

n  Motivation

In the light of the recent wave of Big Data and its Analytics, the Semantic Web-based Trend Analysis on Big Data is quite interesting and beneficial to the researchers as well as the practitioners from engineering to business. In addition, this workshop deals with one of the advancing technologies for Semantic Web-based Big Data Analytics. Specifically, by bringing together representatives of academia and industry, the workshop will be also a means for identifying new research problems and disseminating results of the research and practice.

 

n  Workshop Description

R&D Trend Analysis is to discover and predict technical opportunities and technology trends using Semantic Web technologies to improve the performance of users tasks such as decision making, project management, and R&D planning. However, the analysis and prediction of R&D or business trends from various kinds of Big Data sources such as Web documents, papers and patents could furnish corporations executives or project managers with informative & predictive support for decision making on marketing, sales and product direction. As core technologies for supporting R&D Trend Analysis, Text Mining and Semantic Web have been studied and proven to be effective for decades. So, in this session, we are going to cover all aspects that relate to research and practical issues of Semantic Web-based R&D Trend Analysis on Big Data.

 

Topics of interest for the session will include but will not be limited to:

-       R&D Trend Analysis based on Semantic Web

-       Knowledge Acquisition for R&D Trend Analysis

-       NLP & Text Mining for R&D Trend Analysis

-       Services for R&D Trend Analysis

-       Big Data Management for R&D Trend Analysis

-       Big Data Analytics for R&D Trend Analysis

 

n  Submission Guidelines

-       Authors are invited to submit original papers that MUST NOT have been submitted to or published in any other workshop, conference, or journal.

-       Submissions must be in PDF format, using the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS).

-       Submissions must be no longer than 16 pages for regular paper and 6 pages for short paper.

-       All submissions be submitted via EasyChair.

-       All papers will be reviewed by the Program Committee for significance, originality, accuracy, and clarity.

-       Accepted papers will be distributed to conference attendees and also published by Springer in the printed conference proceedings.

-       At least one author of each accepted paper must register for the conference and present the paper there. 

 

n  Important Dates

-       Submission due: September 30, 2012 October 12, 2012

-       Notification of acceptance: October 20, 2012

-       Final Submission: October 30, 2012

-       Conference: December 2, 2012

 

n  COMMITTEE MEMBERS

Organizing Committee:

     Hanmin Jung,     KISTI, Korea       jhm@kisti.re.kr,

Ing-Xiang Chen, Ericsson Taiwan Ltd., Taiwan, ing-xiang.chen@ericsson.com

Program Committee:

Brahmananda Sapkota

University of Twente, Netherlands

Chengzhi Zhang

Nanjing University of Science and Technology, China

Haklae Kim

Samsung Electronics Inc., Korea

In-Su Kang

Computer Science and Engineering, Kyungsung University, Korea

Kazunari Sugiyama

National University of Singapore, Singapore

Michaela Geierhos

Munich University, Germany

Qing Li

Southwestern University of Finance and Economics (SWUFE), China

Sa-Kwang Song

Korea Institute of Science and Technology Information, Korea

Seung-Hoon Na

National University of Singapore, Singapore

Seungwoo Lee

Korea Institute of Science and Technology Information, Korea

Zhangbing Zhou

Institut TELECOM & Management SudParis, France

Zhixiong Zhang

National Science Library, China

Zhu Lijun

ISTIC, China

Pyung Kim

Jeonju National University of Education, Korea

Dongwon Jeong

Kunsan National University, Korea

Hyunchul Jang

KIOM, Korea

Sung-Kwon Choi

ETRI, Korea

Yeong Su Lee

Munich University, Germany

(to be added)