A Survey on Extractive Knowledge Graph Summarization: Applications, Approaches, Evaluation, and Future Directions

• URL: http://arxiv.org/abs/2402.12001v1
• Date: Mon, 19 Feb 2024 09:49:53 GMT
• Title: A Survey on Extractive Knowledge Graph Summarization: Applications, Approaches, Evaluation, and Future Directions
• Authors: Xiaxia Wang, Gong Cheng
• Abstract summary: extractive KG summarization aims at distilling a compact subgraph with condensed information. We 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.
• Score: 9.668678976640022
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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