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Discovery of Keys for Graphs
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Discovery of Keys for Graphs

Abstract

Keys for graphs specify the topology and value constraints to uniquely identify entities in a graph in applications such as object identification, knowledge fusion, deduplication, and social network reconciliation. Despite their prevalence, existing key mining algorithms do not consider graph keys with recursive key definitions, which capture dependence between entities. We introduce GKMiner$$\mathsf {GKMiner}$$, an algorithm that mines recursive keys over graphs. We show the efficiency and utility of our discovered keys using large-scale, real data graphs.

Authors

Alipourlangouri M; Chiang F

Book title

Big Data Analytics and Knowledge Discovery

Series

Lecture Notes in Computer Science

Volume

13428

Pagination

pp. 202-208

Publisher

Springer Nature

Publication Date

January 1, 2022

DOI

10.1007/978-3-031-12670-3_17
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