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personal data approved: 2020. III. 03.
Personal data
Richárd Farkas
name Richárd Farkas
name of institution
doctoral school
SzTE Doctoral School of Computer Science (Supervisor)
Contact details
E-mail address rfarkasinf.u-szeged.hu
phone number +36 62 546-720
own web page
Academic title
scientific degree, title Ph.D.
year degree was obtained 2010
discipline to which degree belongs computer sciences
institution granting the degree University of Szeged
Employment
2010 - University of Szeged
university professor or researcher
Thesis topic supervisor
number of doctoral students supervised until now 6
number of students who fulfilled course requirements 4
students who obtained their degrees:
(50%) István Nagy PhD 2015  IDI2-SzTE
(50%) Gábor Berend PhD 2014  IDI2-SzTE

completed course requirement, without degree or degree granting in process:
(50%) Gábor Kőrösi (PhD) 2018/08  IDI2-SzTE
(50%) Péter Esztelecki (PhD) 2018/08  IDI2-SzTE
Viktor Hangya (PhD) 2017/08  IDI2-SzTE
Zsolt Szántó (PhD) 2017/08  IDI2-SzTE
present PhD students:
Vanda Balogh (PhD) (2022/08)  IDI2-SzTE
Dániel Kövesi-Nagy (PhD) (2021/08)  IDI2-SzTE
  Thesis topic proposals
Research
research area machine learning, natural language processing, computational linguistics
research field in which current research is conducted computer sciences
mathematics and computing
Publications
2018

Váradi Tamás, Simon Eszter, Sass Bálint, Mittelholcz Iván, Novák Attila, Indig Balázs, Farkas Richárd, Vincze Veronika: E-magyar -- A Digital Language Processing System, In: Nicoletta, Calzolari; Khalid, Choukri; Christopher, Cieri; Thierry, Declerck; Sara, Goggi; Koiti, Hasida; Hitoshi, Isahara; Bente, Maegaard; Joseph, Mariani; Hélène, Mazo; Asuncion, Moreno; Jan, Odijk; Stelios, Piperidis; Takenobu, Tokunaga (szerk.) Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), European Language Resources Association (ELRA) (2018) pp. 1307-1312.
type of document:
number of independent citations: 2
language: English
URL 
2018

Vincze Veronika, Hegedűs Klára, Sliz-Nagy Alex, Farkas Richárd: SzegedKoref: A Hungarian Coreference Corpus, In: Nicoletta, Calzolari; Khalid, Choukri; Christopher, Cieri; Thierry, Declerck; Sara, Goggi; Koiti, Hasida; Hitoshi, Isahara; Bente, Maegaard; Joseph, Mariani; Hélène, Mazo; Asuncion, Moreno; Jan, Odijk; Stelios, Piperidis; Takenobu, Tokunaga (szerk.) Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), European Language Resources Association (ELRA) (2018) pp. 401-405.
type of document:
language: English
2018

Gábor Kórösi, Péter Esztelecki, Farkas Richard, Krisztina Tóth: Clickstream-based outcome prediction in short video MOOCs, In: Proceedings of International Conference on Computer, Information and Telecommunication Systems (CITS) 2018, IEEE (2018) p. 1.
type of document:
language: English
2017

Viktor Hangya, Richárd Farkas: A comparative empirical study on social media sentiment analysis over various genres and languages, ARTIFICIAL INTELLIGENCE REVIEW 47: (4) pp. 485-505.
type of document: Journal paper/Article
number of independent citations: 1
language: English
URL 
2017

Hangya Viktor, Szántó Zsolt, Farkas Richárd: Latent Syntactic Structure-Based Sentiment Analysis, In: IEEE (szerk.) 2017 2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA), IEEE (2017) 10.1109/CIAPP.2017.8167217
type of document:
language: English
URL 
2014

Szántó Z, Farkas R: Special techniques for constituent parsing of morphologically rich languages, In: Gosse, Bouma; Yannick, Parmentier (szerk.) 14th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2014, Association for Computational Linguistics (2014) pp. 135-144.
type of document:
language: English
2013

Fraser A, Schmid H, Farkas R, Wang R, Schütze H: Knowledge sources for constituent parsing of German, a morphologically rich and less-configurational language, COMPUTATIONAL LINGUISTICS 39: (1) pp. 57-85.
type of document:
language: English
URL 
2011

Richárd Farkas: Learning Local Content Shift Detectors from Document-level Information, In: Wanxiang, Che (szerk.) Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, EMNLP 2011, ACL (2011) pp. 759-770.
type of document: Part of book/Proceedings Paper
language: English
2010

Farkas R, Vincze V, Móra Gy, Csirik J, Szarvas Gy: The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text, In: Association, for Computational Linguistics (szerk.) Proceeding of the Fourteenth Conference on Computational Natural Language Learning (CoNLL-2010), Association for Computational Linguistics (2010) pp. 1-12.
type of document:
number of independent citations: 123
language: English
2007

Szarvas GY, Farkas R, Busa-Fekete R: State-of-the-art anonymization of medical records using an iterative machine learning framework, JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 14: (5) pp. 574-580.
type of document: Journal paper/Article
number of independent citations: 75
language: English
URL 
Number of independent citations to these publications:201 
Scientometric data
Saját közlemény- és idézőlista list of publications and citations
number of scientific publications that meet accreditation criteria:
124
number of scientific publications:
124
monographs and professional books:
0
monographs/books in which chapters/sections were contributed:
1 
scientific publications published abroad that meet the accreditation criteria:
70
publications not in Hungarian, published in Hungary, meeting the accreditation criteria:
8
number of independent citations to scientific publications and creative works:
765

 
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. )