András A. Benczúr

2.7k citations
111 papers · 1.4k indexed · h-index 19

András A. Benczúr

102 papers receiving 1.2k citations

Peers

András A. Benczúr
Comparison fields: 5 of 128
  • Information Systems 612
  • Computational Mathematics 12
  • Artificial Intelligence 597
  • Statistical and Nonlinear Physics 197
  • Computational Theory and Mathematics 213
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Countries citing papers authored by András A. Benczúr

Since Specialization
Citations

This map shows the geographic impact of András A. Benczúr'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 András A. Benczúr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites András A. Benczúr more than expected).

Fields of papers citing papers by András A. Benczúr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by András A. Benczúr. 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 András A. Benczúr. The network helps show where András A. Benczúr may publish in the future.

Co-authorship network

The 25 scholars most cited alongside András A. Benczúr, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with András A. Benczúr Line = papers co-authored together András A. Benczúr links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202015
2 201821
3
Alpenglow: Open source recommender framework with time-Aware learning and evaluation
20173
4
Online ranking prediction in non-stationary environments
20173
5
Location-aware online learning for top-k hashtag recommendation
20154
6
DMS-SZTAKI @ ImageCLEF 2012 Photo Annotation.
20124
7
SZTAKI @ ImageCLEF 2009
20091
8
SZTAKI @ TRECVID 2009
20090
9
Web Spam: a Survey with Vision for the Archivist
20084
10
Large-Scale Principal Component Analysis on LiveJournal Friends Network
20086
11
Who Rated What? A Recommender System Benchmark Winner Report.
20081
12
Semi-Supervised Learning: A Comparative Study for Web Spam and Telephone User Churn
200710
13
PageRank és azon túl: Hiperhivatkozások szerepe a keresésben
20061
14
Link-Based Similarity Search to Fight Web Spam
200647
15
SpamRank - fully automatic link spam detection. Work in progress
200521
16
SpamRank -- Fully Automatic Link Spam Detection.
2005118
17 20053
18 19987
19
An Example for an Adaptive Control Method Providing Data Based Integrity
19791
20
On the Bayesian approach to optimal performance of page storage hierarchies.
19772

About András A. Benczúr

András A. Benczúr is a scholar working on Information Systems, Artificial Intelligence and Computer Science Applications, having authored 111 papers that have together received 1.4k indexed citations. Recurring topics across this work include Spam and Phishing Detection (19 papers), Recommender Systems and Techniques (17 papers), Complexity and Algorithms in Graphs (12 papers), Web Data Mining and Analysis (12 papers), Complex Network Analysis Techniques (11 papers), Text and Document Classification Technologies (10 papers), Algorithms and Data Compression (9 papers) and Topic Modeling (8 papers). The work is most often cited by research in Information Systems (612 citations), Computational Mathematics (12 citations) and Artificial Intelligence (597 citations). András A. Benczúr has collaborated with scholars based in Hungary, United States and Finland. Frequent co-authors include Károly Csalogány, David R. Karger, Tamás Sarlós, Róbert Pálovics, István Bíró, Jácint Szabó, Bálint Daróczy, Miklós Erdélyi, Levente Kocsis and Károly Farkas.

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.

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