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pro vyhledávání: '"Belgin Ergenc"'
Akademický článek
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Akademický článek
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Autor:
Büşra Çalmaz, Belgin Ergenç Bostanoğlu
Publikováno v:
PeerJ Computer Science, Vol 10, p e2501 (2024)
Clique counting is a crucial task in graph mining, as the count of cliques provides different insights across various domains, social and biological network analysis, community detection, recommendation systems, and fraud detection. Counting cliques
Externí odkaz:
https://doaj.org/article/4828b8843a704250b27134b1d60a0cfe
Publikováno v:
PeerJ Computer Science, Vol 10, p e2361 (2024)
Frequent subgraph mining (FSM) is an essential and challenging graph mining task used in several applications of the modern data science. Some of the FSM algorithms have the objective of finding all frequent subgraphs whereas some of the algorithms f
Externí odkaz:
https://doaj.org/article/adf9017876054ccaaa8f05d3589299e1
Autor:
Belgin Ergenc, Ahmet Cumhur Öztürk
Publikováno v:
International Journal of Data Warehousing and Mining. 14:37-59
This article describes how association rule mining is used for extracting relations between items in transactional databases and is beneficial for decision-making. However, association rule mining can pose a threat to the privacy of the knowledge whe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e60386ff2c039ee73a92b4e1571e3cf3
https://doi.org/10.4018/ijdwm.2018040103
https://doi.org/10.4018/ijdwm.2018040103
Akademický článek
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Autor:
Sadeq Darrab, Belgin Ergenc
Publikováno v:
KES
21st International Conference on Knowledge - Based and Intelligent Information and Engineering Systems, KES 2017; Saint Charles Campus of Aix-Marseille UniversityMarseille; France; 6 September 2017 through 8 September 2017
Frequent pattern minin
Frequent pattern minin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::978eec6dd35d69e6a6b73bfbb42d0ab2
https://doi.org/10.1016/j.procs.2017.08.051
https://doi.org/10.1016/j.procs.2017.08.051
Autor:
Leyla Tekin, Belgin Ergenç Bostanoğlu
Publikováno v:
Symmetry, Vol 16, Iss 10, p 1272 (2024)
Community detection enables the discovery of more connected segments of complex networks. This capability is essential for effective network analysis. But, it raises a growing concern about the disclosure of user privacy since sensitive information m
Externí odkaz:
https://doaj.org/article/aee8bfa583594d85aca50987bbcf95a2
Autor:
Büşra Çalmaz, Belgin Ergenç Bostanoğlu
Publikováno v:
Symmetry, Vol 16, Iss 8, p 983 (2024)
Clique counts are crucial in applications like detecting communities in social networks and recurring patterns in bioinformatics. Counting k-cliques—a fully connected subgraph with k nodes, where each node has a direct, mutual, and symmetric relati
Externí odkaz:
https://doaj.org/article/78bba22279a4484fa0753a8903c56a49
Autor:
Nourhan N. Abuzayed, Belgin Ergenc
Publikováno v:
IDEAS
21st International Database Engineering and Applications Symposium, IDEAS 2017; Bristol; United Kingdom; 12 July 2017 through 14 July 2017
Mining1 frequent itemsets is an important part of association rule mining process. Handling dynamic aspect
Mining1 frequent itemsets is an important part of association rule mining process. Handling dynamic aspect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f9ce06c7a550a27eb5cc32d5f97f943
http://hdl.handle.net/11147/6460
http://hdl.handle.net/11147/6460
