The 2nd International Workshop on
Knowledge Graph Management and Applications
(KGMA 2019)
In recent years, an increasing number of large-scale knowledge graphs have been constructed and published on the Web, by both academic and industrial communities, such as DBpedia, YAGO, Freebase, Wikidata, Google Knowledge Graph, Microsoft Satori, Facebook Entity Graph, and others. In fact, a knowledge graph is essentially a large network of entities, their properties, and semantic relationships between entities. Such kind of graph-based knowledge data has been posing a great challenge to the traditional data management theories and technologies. On the other hand, the database community has been putting a lot of effort into graph databases for nearly two decades to make the storage, query processing, mining, and analysis of large graph data more efficient and scalable. However, there are still gaps between the requirements of knowledge graph applications from various domains and the current state of techniques in graph databases. Therefore, this workshop aims to bring together researchers, practitioners, developers, and users from knowledge graph research and application, graph database, social network, and other relevant communities to address the challenges, present state-of-the-art solutions, exchange ideas and results, and discuss future research directions in management, analysis, and application of knowledge graphs in different domains.
Accepted papers will be published in a Springer LNCS proceeding volume along with APWeb-WAIM proceedings.
The topics of interest include, but are not limited to the following:
- Knowledge graph information extraction
- Knowledge graph data integration
- Knowledge graph construction
- Knowledge graphs and knowledge representation
- Knowledge graphs and knowledge bases
- Knowledge graphs and knowledge engineering
- Knowledge graphs and ontologies
- Knowledge graphs in social networks
- Probabilistic and uncertain knowledge graphs
- Knowledge graph storage and indexing
- RDF graph storage and indexing
- Graph database storage scheme
- Distributed knowledge graph storage and indexing
- Relational-based knowledge graph storage and indexing
- Graph pattern matching
- Reachability query processing
- Shortest path query processing
- Regular path query processing
- Navigational query processing
- Graph query languages
- Distributed/parallel graph query processing
- Knowledge graph query processing and benchmarking
- Knowledge graph embedding and representational learning
- Graph classification
- Graph clustering
- Graph frequent pattern mining
- Link prediction in knowledge graphs
- Outlier detection in knowledge graphs
- Deep learning on knowledge graphs
- Knowledge graph data visualization
- Social network analysis using knowledge graphs
- Knowledge-graph based inference and reasoning
- Knowledge-graph based information retrieval
- Knowledge-graph based recommendation systems
- User interfaces of knowledge-graph based systems
- Questing answering using knowledge graphs
- Knowledge-graph based intelligent systems
- Knowledge-graph based information systems
- Knowledge graphs and natural language processing
- Biological and biomedical knowledge graphs
- Knowledge-graph based bioinformatics
- Security, privacy, and trust on knowledge graphs