This workshop is in conjunction with 2017 IEEE International Conference on Big Knowledge (ICBK 2017)http://dmic.hfut.edu.cn/ICBK2017/ICBK2017/cfp.html

The Web has developed into a global information space consisting not just of linked documents, but also of Linked Data. The Linked Open Data (LOD) Cloud has gained significant traction over the past years. As of February 2017, LOD community has 1146 interlinked datasets covering diverse domains from life sciences to government data. Large-scale Linked Data has the potential to support a variety of applications ranging from open domain question answering to knowledge discovery. Thus, there has been a tremendous body of ongoing work on researches that consume Linked Data from the Web. Since Linked Data is one of the most fundamental structures to semantic web and knowledge graph, a perspective is new technologies could be developed based on Linked Data Mining (LDM).

LDM is open to covering all topics related to Linked Data publication and consumption, and especially interested in researches such as entity consolidation, association discovery, data integration, quality evaluation, search and query, and Linked Spatiotemporal Data analysis. Besides, how to achieve efficient, accurate and trustworthy mining on Linked Data has become crucial of importance that significantly impacts its future success and practical applications. LDM is looking for novel and significant research contributions addressing theoretical, analytical and empirical aspects of Linked Data together with descriptions of applied and validated industry solutions as tools, systems or architecture that benefit to Linked Data mining.This workshop aims to bring together researchers and practitioners to discuss various aspects of LDM, and report the latest academic and industrial research results related to LDM.

Topics of interest include, but are not limited to:

Machine learning and data mining in Linked Data
knowledge discovery in Linked data and ontologies
Visual analytics and visualization of Linked Data
Data quality, validation and data trustworthiness
Dynamics and evolution of LD
Trust, privacy, Provenance and security of Linked Datag
Search, query and analysis in Linked Data
Scalability issues relating to Linked Data
Extraction, linking and integration of LD
Interoperation of Linked Spatiotemporal Data
Applications of Linked Data on real-world problems

Important Dates

Paper submission deadline: May 10th, 2017
Author notification: May 30th, 2017
Final manuscript due: June 15th, 2017

Submission Instructions

Submitted papers must not substantially overlap with papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings. Papers submitted LDM2017 should be written in English conforming to the IEEE 2-column format. The paper should be submitted (https://wi-lab.com/cyberchair/2017/icdm17/scripts/submit.php?subarea=S02&undisplay_detail=1&wh=/cyberchair/2017/icdm17/scripts/ws_submit.php) the cyberchair paper submission system at the workshop website. The length of the papers should not exceed 8 pages, including tables, figures, references and appendixes.

All accepted workshop papers will be published in the main conference proceedings by the IEEE Computer Society.
Submitting a paper to LDM 2017 means that, if the paper is accepted, at least one author should attend the workshop and present the paper.

Program Co-Chairs
Jun Liu, Xi’an Jiaotong University, China (liukeen@mail.xjtu.edu.cn)
Zheng Yan, Aalto University, Finland / Xidian University, China (zheng.yan@aalto.fi)

PC Members (In alphabetical order)
Garimella Rama Murthy, The International Institute of Information Technology, Hyderabad (IIIT-H), India
Haifei Max Li, Union University, USA
Qingtang Liu,Central China Normal University,China
Wei Zhang, Amazon Inc., USA
Ye Tian,China Internet Network Information Center (CNNIC),China

Contact

Please email inquiries concerning LDM 2017 to:
Prof.Jun Liu, Email: liukeen@mail.xjtu.edu.cn