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.