Abstract
Users rely on open data portals and search engines to find open knowledge graphs (KGs). However, existing systems only provide metadata-based KG search but ignore the contents of KGs, i.e., triples. In this paper, we present one of the first content-based search engines for open KGs. Our system CKGSE supports keyword-based KG search, KG snippet generation, KG profiling and browsing, all computed over KGs’ (large) contents rather than their (small) metadata. We implement a prototype with Chinese KGs crawled from OpenKG.CN and we report some preliminary results about the practicability of such a system.
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This work was supported by the NSFC (62072224).
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Wang, X., Lin, T., Luo, W., Cheng, G., Qu, Y. (2021). Content-Based Open Knowledge Graph Search: A Preliminary Study with OpenKG.CN. In: Qin, B., Jin, Z., Wang, H., Pan, J., Liu, Y., An, B. (eds) Knowledge Graph and Semantic Computing: Knowledge Graph Empowers New Infrastructure Construction. CCKS 2021. Communications in Computer and Information Science, vol 1466. Springer, Singapore. https://doi.org/10.1007/978-981-16-6471-7_8
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