Abstract
With the continuous growth of large Knowledge Graphs (KGs), extractive KG summarization becomes a trending task. Aiming at distilling a compact subgraph with condensed information, it facilitates various downstream KG-based tasks. In this survey paper, we are among the first to provide a systematic overview of its applications and define a taxonomy for existing methods from its interdisciplinary studies. Future directions are also laid out based on our extensive and comparative review.
Keywords
- Data Mining: DM: Knowledge graphs and knowledge base completion
- Data Mining: DM: Mining graphs
- Knowledge Representation and Reasoning: KRR: Semantic Web
