Lukács László
Impact in
Papers in
-
- Text and Document Classification Technologies 1
- Imbalanced Data Classification Techniques 1
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- Spam and Phishing Detection 2
- Co-authors
- Andrew Tomkins (1 shared paper)Vivek Ramavajjala (1 shared paper)Peter Young (1 shared paper)Karol Kurach (1 shared paper)Miklós Bálint (1 shared paper)Greg S. Corrado (1 shared paper)Tobias Kaufmann (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)SZTAKI Publication Repository (Hungarian Academy of Sciences) (1 paper)
- Partner nations
- HungaryGreeceUnited States
In The Last Decade
Lukács László
6 papers receiving 144 citations
Peers
Comparison fields: 5 of 44
- Human-Computer Interaction 17
- Health Informatics 4
- Artificial Intelligence 85
- Information Systems and Management 17
- Information Systems 46
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 | 114 | |
| 2 | 2007 | 23 | |
| 3 | Semi-Supervised Learning: A Comparative Study for Web Spam and Telephone User Churn | 2007 | 10 |
| 4 | A Föld aknaproblémája és a megoldás lehetőségei, különös tekintettel a Magyar Honvédség közreműködésének javasolható irányaira III. | 1998 | 1 |
| 5 | 2013 | 1 | |
| 6 | 1997 | 1 | |
| 7 | 2013 | 0 |
About Lukács László
Lukács László is a scholar working on Artificial Intelligence, Information Systems, Political Science and International Relations, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 7 papers that have together received 150 indexed citations. Recurring topics across this work include Spam and Phishing Detection (2 papers), Complex Network Analysis Techniques (1 paper), Boron and Carbon Nanomaterials Research (1 paper), Personal Information Management and User Behavior (1 paper), Advanced Data Compression Techniques (1 paper), Text and Document Classification Technologies (1 paper), Imbalanced Data Classification Techniques (1 paper) and Hungarian Social, Economic and Educational Studies (1 paper). The work is most often cited by research in Human-Computer Interaction (17 citations), Health Informatics (4 citations), Artificial Intelligence (85 citations), Information Systems and Management (17 citations) and Information Systems (46 citations). Lukács László has collaborated with scholars based in Hungary, Greece and United States. Frequent co-authors include Andrew Tomkins, Vivek Ramavajjala, Peter Young, Karol Kurach, Miklós Bálint, Greg S. Corrado, Tobias Kaufmann, Anjuli Kannan, András A. Benczúr and Károly Csalogány. Their work appears in journals such as Internet Research, International Studies in Catholic Education, Materials science forum and SZTAKI Publication Repository (Hungarian Academy of Sciences).
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.