@article{MTMT:33855058,
	title = {Digitized Value Chain in Food Industries: Opportunities and Challenges for SMEs},
	url = {https://m2.mtmt.hu/api/publication/33855058},
	author = {CHHABRA, AASHIMA and Botos, Szilvia and Felföldi, János},
	journal-iso = {SEFBIS J},
	journal = {SEFBIS JOURNAL},
	volume = {2023},
	unique-id = {33855058},
	issn = {1788-2265},
	year = {2023},
	orcid-numbers = {Botos, Szilvia/0000-0003-4873-1032; Felföldi, János/0000-0002-3895-6636}
}

@article{MTMT:33720205,
	title = {Economical Traffic Analysis Methods},
	url = {https://m2.mtmt.hu/api/publication/33720205},
	author = {Erdős, Ferenc and Elshebli, Enas},
	doi = {10.14267/SEFBIS.2023.01},
	journal-iso = {SEFBIS J},
	journal = {SEFBIS JOURNAL},
	volume = {2023},
	unique-id = {33720205},
	issn = {1788-2265},
	year = {2023}
}

@article{MTMT:32826031,
	title = {Online Learning in the COVID-19 Pandemic. Catastrophe or Opportunity?},
	url = {https://m2.mtmt.hu/api/publication/32826031},
	author = {Huang, Xin},
	doi = {10.14267/SEFBIS.2022.02},
	journal-iso = {SEFBIS J},
	journal = {SEFBIS JOURNAL},
	unique-id = {32826031},
	issn = {1788-2265},
	year = {2022}
}

@article{MTMT:33681600,
	title = {The impact of COVID-19 on work performance, organizational communication and cyber security in the IT sector at enterprise level},
	url = {https://m2.mtmt.hu/api/publication/33681600},
	author = {Németh, Richárd},
	journal-iso = {SEFBIS J},
	journal = {SEFBIS JOURNAL},
	volume = {SEFBIS:2022:01},
	unique-id = {33681600},
	issn = {1788-2265},
	abstract = {As a result of COVID-19, we have all seen an increase in stress due to the lifestyle and organizational changes
		brought about by the crisis, a sharp depreciation of social relationships and a transformation in human relations
		and communication at work. In my study, I sought to answer the question of how the measures introduced to
		protect against COVID-19 and the mandatory home office induced changes in work and working conditions in
		the corporate sector.},
	year = {2022},
	pages = {1-10}
}

@article{MTMT:32737475,
	title = {Monitoring the Duration of Use of Web-based Systems Using Clustering Procedures},
	url = {https://m2.mtmt.hu/api/publication/32737475},
	author = {Mátyus, Bálint},
	journal-iso = {SEFBIS J},
	journal = {SEFBIS JOURNAL},
	volume = {2021},
	unique-id = {32737475},
	issn = {1788-2265},
	year = {2021},
	pages = {2-14}
}

@article{MTMT:32683657,
	title = {Ticketing Data Warehouse System Development. Challenges and Experiences},
	url = {https://m2.mtmt.hu/api/publication/32683657},
	author = {Molnár, Géza},
	journal-iso = {SEFBIS J},
	journal = {SEFBIS JOURNAL},
	volume = {2021},
	unique-id = {32683657},
	issn = {1788-2265},
	year = {2021},
	pages = {14-24}
}

@article{MTMT:30845068,
	title = {A New Approach and Framework for Risk Assessment Maturity},
	url = {https://m2.mtmt.hu/api/publication/30845068},
	author = {Abazi, Blerton},
	journal-iso = {SEFBIS J},
	journal = {SEFBIS JOURNAL},
	volume = {13},
	unique-id = {30845068},
	issn = {1788-2265},
	year = {2019},
	pages = {62-72}
}

@article{MTMT:30845005,
	title = {The Impact of Industry 4.0 to the ERP Approach},
	url = {https://m2.mtmt.hu/api/publication/30845005},
	author = {Gërvalla, Muhamet and Ternai, Katalin},
	journal-iso = {SEFBIS J},
	journal = {SEFBIS JOURNAL},
	volume = {13},
	unique-id = {30845005},
	issn = {1788-2265},
	year = {2019},
	pages = {56-62}
}

@article{MTMT:30843835,
	title = {Solving Exercise Generation Problems Using the Improved EGAL Metaheuristic Algorithm},
	url = {https://m2.mtmt.hu/api/publication/30843835},
	author = {Láng, Blanka},
	journal-iso = {SEFBIS J},
	journal = {SEFBIS JOURNAL},
	volume = {13},
	unique-id = {30843835},
	issn = {1788-2265},
	year = {2019},
	pages = {23-31}
}

@article{MTMT:30843795,
	title = {A Comparative Study of Antminer+ and Decision Tree Classification Performances},
	url = {https://m2.mtmt.hu/api/publication/30843795},
	author = {Brunner, Csaba},
	journal-iso = {SEFBIS J},
	journal = {SEFBIS JOURNAL},
	volume = {13},
	unique-id = {30843795},
	issn = {1788-2265},
	abstract = {There is an increasing demand for knowledge discovery from large datasets. One of the more common extraction
		types is classification, placing entities into categories based on how similar their features are. Many new
		algorithms are experimented with, one example is antminer+. It is a swarm intelligence-based approach, modeling
		an ant colony’s foraging behavior. A key question is, how well it performs on benchmark data compared to
		a known data mining algorithm. The answer depends on the classification metric of choice; it can achieve results
		comparable to other data mining algorithms.},
	year = {2019},
	pages = {15-23}
}