Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/9516
Title: A qualitative survey on frequent subgraph mining
Authors: Güvenoğlu, Büşra
Ergenç Bostanoğlu, Belgin
Keywords: Frequent subgraph mining
Graph mining
Data mining
Issue Date: 2018
Publisher: De Gruyter
Abstract: Data mining is a popular research area that has been studied by many researchers and focuses on finding unforeseen and important information in large databases. One of the popular data structures used to represent large heterogeneous data in the field of data mining is graphs. So, graph mining is one of the most popular subdivisions of data mining. Subgraphs that are more frequently encountered than the user-defined threshold in a database are called frequent subgraphs. Frequent subgraphs in a database can give important information about this database. Using this information, data can be classified, clustered and indexed. The purpose of this survey is to examine frequent subgraph mining algorithms (i) in terms of frequent subgraph discovery process phases such as candidate generation and frequency calculation, (ii) categorize the algorithms according to their general attributes such as input type, dynamicity of graphs, result type, algorithmic approach they are based on, algorithmic design and graph representation as well as (iii) to discuss the performance of algorithms in comparison to each other and the challenges faced by the algorithms recently.
Description: WOS: 000473498200001
URI: https://doi.org/10.1515/comp-2018-0018
https://hdl.handle.net/11147/9516
ISSN: 2299-1093
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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