Research Article
Approximate Sub-graph Matching over Knowledge Graph
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@INPROCEEDINGS{10.1007/978-3-030-64214-3_14, author={Jiyuan Ren and Yangfu Liu and Yi Shen and Zhe Wang and Zhen Luo}, title={Approximate Sub-graph Matching over Knowledge Graph}, proceedings={Mobile Computing, Applications, and Services. 11th EAI International Conference, MobiCASE 2020, Shanghai, China, September 12, 2020, Proceedings}, proceedings_a={MOBICASE}, year={2020}, month={12}, keywords={Knowledge graph Sub-graph matching Compression Skyline}, doi={10.1007/978-3-030-64214-3_14} }- Jiyuan Ren
Yangfu Liu
Yi Shen
Zhe Wang
Zhen Luo
Year: 2020
Approximate Sub-graph Matching over Knowledge Graph
MOBICASE
Springer
DOI: 10.1007/978-3-030-64214-3_14
Abstract
With the rapid development of the mobile internet, the volume of data has grown exponentially, and the content of data become more complicated. It is hard for people to select useful information from such a large number of data. In this paper, we study the problem of approximate sub-graph matching over knowledge graph. We first propose two algorithms to reduce the scale of knowledge graph. Next, we use an efficient algorithm to find similarity sub-graphs. Thirdly, we use skyline technique to further select high quality sub-graphs from the matching results. Theoretical analysis and extensive experimental results demonstrate the effectiveness of the proposed algorithms.
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