FastAGEDs: Fast Approximate Graph Entity Dependency discovery

Guangtong Zhou, Selasi Kwashie, Yidi Zhang, Michael Bewong, Vincent M. Nofong, Junwei Hu, Debo Cheng, Keqing He, Shanmei Liu, Zaiwen Feng

Research output: Book chapter/Published conference paperConference paperpeer-review

1 Citation (Scopus)
9 Downloads (Pure)


This paper studies the discovery of approximate rules in property graphs. First, we propose a semantically meaningful measure of error for mining graph entity dependencies (GEDs) that almost hold, to tolerate errors and inconsistencies that exist in real-world graphs. Second, we present a new characterisation of GED satisfaction, and devise a depth-first search strategy to traverse the search space of candidate GEDs efficiently. Further, we perform experiments to demonstrate the feasibility and scalability of our solution, FastAGEDs, with three real-world graphs. The results show FastAGEDs is effective and efficient for mining approximate GEDs in noisy and erroneous real-world graphs.

Original languageEnglish
Title of host publicationWeb Information Systems Engineering – WISE 2023
Subtitle of host publication24th International Conference Melbourne, VIC, Australia, October 25–27, 2023 Proceedings
EditorsFeng Zhang, Hua Wang, Mahmoud Barhamgi, Lu Chen, Rui Zhou
Place of PublicationSingapore
Number of pages15
ISBN (Electronic)9789819972548
ISBN (Print)9789819972531
Publication statusPublished - 2023
Event24th International Conference on Web Information Systems Engineering, WISE 2023 - City Campus of Victoria University, Melbourne, Australia
Duration: 25 Oct 202327 Oct 2023 (Conference website) (Program)

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14306 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference24th International Conference on Web Information Systems Engineering, WISE 2023
OtherWISE Society has established itself as a solid community aiming at high-quality research and offering the ground for advancing and progressing efforts in Web information systems addressed topics. The aim of the conference series on Web Information Systems Engineering is to provide an international forum for researchers, professionals, and industrial practitioners to share their knowledge and insights in the rapidly growing area of Web technologies, methodologies, and applications. WISE’s particular topics of interest include but not restricted to: big data techniques and applications, blockchain technologies, cloud computing, deep/hidden web, future internet architectures and protocols, human factors and social issues, integration of web and internet-connected objects, linked open data, machine learning for the web, mobile web, peer-computing, search, text and media extraction, clustering and classification of the web, semantic web, social networks computing, social web and applications, social web models, analysis and mining, visualization for the web and rich web UI, web agents and web intelligence, web-based applications (e.g., e-commerce, e-government, and e-learning), web-based business processes and web services, web-based enterprise systems, web data integration and mashups, web data models, web engineering, metrics and performance, web information retrieval, web mining and web warehousing, web privacy management, web security and trust management, web tools and languages.
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