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BDQM 2016 : The 1st International Workshop on Big Data Quality Management | |||||||||||||||
Link: http://theory.utdallas.edu/DASFAA2016/BDQM-CFP.docx | |||||||||||||||
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Call For Papers | |||||||||||||||
Call for Papers
1st Workshop on Big Data Quality Management @ DASFAA 2016 16-19 April 2016, Dallas, TX, USA With the development of information technology, big data arise in various applications and areas. On one hand, big data bring new value. On the other hand, new challenges are brought. One of the challenges is the data quality problem. The features of big data bring more serious data quality problems. Due to volume, the harvest, storage, transmission and computation will cause more errors. Current data get outdated for velocity. The variety leads to more inconsistency and conflicts. Data quality problem will do harm to the applications of big data, even result in disaster. As a result, big data quality management is in demand to decrease the harm of data quality problems and computes high-quality problem from big data. Big data management has become one of the hottest issues not only in database community but also in artificial intelligence, data mining and other related area. The goal of the Workshop on Big Data Quality Management is to raise the awareness of quality issues in Big data and promote approaches to evaluate and improve big data quality. The workshop topics include, but are not limited to: Data Quality Models and Theory Data Quality Measures and Evaluations Data Cleaning Algorithms Record Linkage and Entity Resolution Privacy Preservation and Security Issues in the Process of Data Cleaning Data Quality Policies and Standards Data Provenance and Annotation Data Quality in Information Retrieval and Extraction Probabilistic, Fuzzy, and Uncertain Data Management Data Quality in Sensor Networks and CPS Data Quality in Information Integration Crowdsourcing for Data Quality Master Data Management Applications for Data Quality Management Error-Tolerate Computation Submission guidelines We seek novel technical research papers in the context of Data Quality Management with a length of up to 8 pages (long) and 4 pages (short) papers. Papers should be submitted in PDF format. Paper submissions should be formatted in the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS). Please submit your paper via cmt at https://cmt3.research.microsoft.com/BDQM2016. Submissions will be peer reviewed by three independent reviewers. Accepted papers have to be presented at the workshop to be published in the proceedings. Proceedings will be published in the Springer LNCS series. Important Dates All deadlines are, unless otherwise stated, at 23:59 Hawaii time. Submission of research papers: DEC 1, 2015. Notification of paper acceptance: Jan 15, 2016 Submission of camera-ready papers: Jan 31, 2016 Honorable Chair Jianzhong Li, Harbin Institute of Technology Chair Hongzhi Wang, Harbin Institute of Technology Jing Gao, University at Buffalo, the State University of New York Program Committees (Tentative) Xiaochun Yang, Northeast University Yueguo Chen, Renmin University Nan Tang, QCIR Jiannan Wang, Simon Fraser University Xianmin Liu, Harbin Institute of Technology Zhijing Qin, Pinterest Guoliang Li, Tsinghua University Cheqing Jin, East China Normal University Wenjie Zhang, University of New South Wales Shuai Ma, Beihang University Zhaonian Zou, Harbin Institute of Technology |
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