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personal data approved: 2021. XII. 02.
Personal data
Ágnes Fogarassyné Vathy
name Ágnes Fogarassyné Vathy
name of institution
doctoral school
PE Doctoral School of Information Science and Technology (Supervisor)
Contact details
E-mail address vathydcs.uni-pannon.hu
phone number +36 88 624-712
own web page
Academic title
scientific degree, title Ph.D.
year degree was obtained 2009
discipline to which degree belongs computer sciences
institution granting the degree Eötvös Lóránd University
Employment
1998 - University of Pannonia
university professor or researcher
Thesis topic supervisor
number of doctoral students supervised until now 4
number of students who fulfilled course requirements 1.5
students who obtained their degrees:
(50%) Dániel Leitold PhD 2020  DSIST-PE

students with degree granting in process:
Szabolcs Szekér PhD (2023/01)  DSIST-PE
present PhD students:
(50%) Tamás Miseta (PhD) (2026/01)  DSIST-PE
(50%) Attila Knolmajer (PhD) (2025/08)  DSIST-PE
(50%) Gábor Arányi (PhD) (2025/08)  DSIST-PE
János Kontos (PhD) (2024/08)  DSIST-PE
  Thesis topic proposals
Research
research area data mining, data mining technologies in healthcare, machine learning, predictive analytics
research field in which current research is conducted computer sciences
Publications
2019

Leitold Daniel, Vathy-Fogarassy Agnes, Abonyi Janos: Evaluation of the Complexity, Controllability and Observability of Heat Exchanger Networks Based on Structural Analysis of Network Representations, ENERGIES 12: (3) pp. 1-24.
type of document: Journal paper/Article
number of independent citations: 11
language: English
URL 
2019

Fogarassy György, Vathy-Fogarassy Ágnes, Kenessey István, Kásler Miklós, Forster Tamás: Risk prediction model for long-term heart failure incidence after epirubicin chemotherapy for breast cancer–A real-world data-based, nationwide classification analysis, INTERNATIONAL JOURNAL OF CARDIOLOGY 285: pp. 47-52.
type of document: Journal paper/Article
number of independent citations: 11
language: English
URL 
2017

Dániel Leitold, Ágnes Vathy-Fogarassy, János Abonyi: Controllability and observability in complex networks – the effect of connection types, SCIENTIFIC REPORTS 7: 151
type of document: Journal paper/Article
number of independent citations: 36
language: English
URL 
2017

Vathy-Fogarassy Ágnes, Hugyák Tamás: Uniform data access platform for SQL and NoSQL database systems, INFORMATION SYSTEMS 69: pp. 93-105.
type of document: Journal paper/Article
number of independent citations: 40
language: English
URL 
2017

Krisztina Tóth, Károly Machalik, György Fogarassy, Ágnes Vathy-Fogarassy: Applicability of Process Mining in the Exploration of Healthcare Sequences, In: Szakál, Anikó (szerk.) IEEE 30th Jubilee Neumann Colloquium : Neumann Colloquium 2017, Óbudai Egyetem (2017) pp. 151-155.
type of document: Part of book/Proceedings Paper
number of independent citations: 9
language: English
URL 
2016

András Király, Ágnes Vathy-Fogarassy, János Abonyi: Geodesic distance based fuzzy c-medoid clustering – searching for central points in graphs and high dimensional data, FUZZY SETS AND SYSTEMS 286: pp. 157-172.
type of document: Journal paper/Article
number of independent citations: 15
language: English
URL 
2013

Ágnes Vathy-Fogarassy, János Abonyi: Graph-Based Clustering and Data Visualization Algorithms, Springer-Verlag Wien
type of document: Book/Monography
number of independent citations: 45
language: English
URL 
2009

Vathy-Fogarassy A, Abonyi J: Local and global mappings of topology representing networks, INFORMATION SCIENCES 179: (21) pp. 3791-3803.
type of document: Journal paper/Article
number of independent citations: 14
language: English
URL 
2007

Vathy-Fogarassy A, Feil B, Abonyi J: Minimal Spanning Tree based Fuzzy Clustering, WORLD ACADEMY OF SCIENCE ENGINEERING AND TECHNOLOGY 1: (8) pp. 7-12.
type of document: Journal paper/Article
number of independent citations: 28
language: English
2006

Vathy-Fogarassy A, Kiss A, Abonyi J: Hybrid minimal spanning tree and mixture of gaussians based clustering algorithm, LECTURE NOTES IN COMPUTER SCIENCE 3861: pp. 313-330.
type of document: Journal paper/Article
number of independent citations: 40
language: English
URL 
Number of independent citations to these publications:249 
Scientometric data
list of publications and citations
number of scientific publications that meet accreditation criteria:
89
number of scientific publications:
89
monographs and professional books:
3
monographs/books in which chapters/sections were contributed:
3 
scientific publications published abroad that meet the accreditation criteria:
39
publications not in Hungarian, published in Hungary, meeting the accreditation criteria:
24
number of independent citations to scientific publications and creative works:
383

 
All rights reserved © 2007, Hungarian Doctoral Council. Doctoral Council registration number at commissioner for data protection: 02003/0001. Program version: 2.2358 ( 2017. X. 31. )