Lukács László
Impact in
Papers in
-
- Imbalanced Data Classification Techniques 1
- Advanced Clustering Algorithms Research 1
- Topic Modeling 1
- Algorithms and Data Compression 1
-
- Complex Network Analysis Techniques 3
- Co-authors
- András A. Benczúr (4 shared papers)Károly Csalogány (4 shared papers)Karol Kurach (1 shared paper)Miklós Bálint (1 shared paper)Tobias Kaufmann (1 shared paper)Vivek Ramavajjala (1 shared paper)Greg S. Corrado (1 shared paper)Anjuli Kannan (1 shared paper)
- Journals
- Internet Research (1 paper)International Studies in Catholic Education (1 paper)Materials science forum (1 paper)Lecture notes in computer science (1 paper)Bolyai Society mathematical studies (1 paper)
- Partner nations
- HungaryUnited StatesGreece
In The Last Decade
Lukács László
8 papers receiving 188 citations
Peers
Comparison fields: 5 of 50
- Health Informatics 5
- Human-Computer Interaction 20
- Artificial Intelligence 106
- Statistical and Nonlinear Physics 37
- Information Systems and Management 19
Countries citing papers authored by Lukács László
This map shows the geographic impact of Lukács László's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lukács László with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lukács László more than expected).
Fields of papers citing papers by Lukács László
This network shows the impact of papers produced by Lukács László. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lukács László. The network helps show where Lukács László may publish in the future.
Co-authors
The 12 scholars most cited alongside Lukács László, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 134 | |
| 2 | 2007 | 31 | |
| 3 | 2009 | 12 | |
| 4 | Semi-Supervised Learning: A Comparative Study for Web Spam and Telephone User Churn | 2007 | 11 |
| 5 | 2008 | 3 | |
| 6 | A Föld aknaproblémája és a megoldás lehetőségei, különös tekintettel a Magyar Honvédség közreműködésének javasolható irányaira III. | 1998 | 1 |
| 7 | 1997 | 1 | |
| 8 | 2013 | 1 | |
| 9 | 2013 | 0 |
About Lukács László
Lukács László is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Information Systems, Computer Networks and Communications and Political Science and International Relations, having authored 9 papers that have together received 194 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (3 papers), Spam and Phishing Detection (2 papers), Imbalanced Data Classification Techniques (1 paper), Advanced Clustering Algorithms Research (1 paper), Hungarian Social, Economic and Educational Studies (1 paper), Topic Modeling (1 paper), Advanced Data Compression Techniques (1 paper) and Algorithms and Data Compression (1 paper). The work is most often cited by research in Health Informatics (5 citations), Human-Computer Interaction (20 citations), Artificial Intelligence (106 citations), Statistical and Nonlinear Physics (37 citations) and Information Systems and Management (19 citations). Lukács László has collaborated with scholars based in Hungary, United States and Greece. Frequent co-authors include András A. Benczúr, Károly Csalogány, Karol Kurach, Miklós Bálint, Tobias Kaufmann, Vivek Ramavajjala, Greg S. Corrado, Anjuli Kannan, Andrew Tomkins and Peter Young. Their work appears in journals such as Internet Research, International Studies in Catholic Education, Materials science forum, Lecture notes in computer science and Bolyai Society mathematical studies.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.