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

Xiaxia Wang; Gong Cheng

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arXiv · 2402.12001

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

Xiaxia Wang·Gong Cheng

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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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Xiaxia Wang, Gong Cheng. 2024-02-19. A Survey on Extractive Knowledge Graph Summarization: Applications, Approaches, Evaluation, and Future Directions. https://arxiv.org/abs/2402.12001

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