CheetahKG: A Demonstration for Core-based Top-k Frequent Pattern Discovery on Knowledge Graphs
38th IEEE International Conference on Data Engineering, ICDE 2022
; 2022-May:3134-3137, 2022.
Article
in English
| Scopus | ID: covidwho-2018818
ABSTRACT
Knowledge graphs capture the complex relationships among various entities, which can be found in various real world applications, e.g., Amazon product graph, Freebase, and COVID-19. To facilitate the knowledge graph analytical tasks, a system that supports interactive and efficient query processing is always in demand. In this demonstration, we develop a prototype system, CheetahKG, that embeds with our state-of-the-art query processing engine for the top-k frequent pattern discovery. Such discovered patterns can be used for two purposes, (i) identifying related patterns and (ii) guiding knowledge exploration. In the demonstration sessions, the attendees will be invited to test the efficiency and effectiveness of the query engine and use the discovered patterns to analyze knowledge graphs on CheetahKG. © 2022 IEEE.
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Scopus
Language:
English
Journal:
38th IEEE International Conference on Data Engineering, ICDE 2022
Year:
2022
Document Type:
Article
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