Ilya Markov

1.2k citations
31 papers · 533 · h-index 12

Impact in

Papers in

Ilya Markov

30 papers receiving 512 citations

Peers

Ilya Markov
Comparison fields: 5 of 54
  • Information Systems 366
  • Computer Science Applications 53
  • Management Science and Operations Research 113
  • Artificial Intelligence 256
  • Computer Vision and Pattern Recognition 118
Replace Justin Basilico with:
Justin Basilico United States
Aleksandr Chuklin Netherlands
Maheedhar Kolla Canada
Álvaro Barreiro Spain
Jesús Bernal Spain
Bo Long United States
Jinmook Kim United States
Zhuoye Ding China
Adith Swaminathan United States
Hande Dong China
Ilya Markov relative to Justin Basilico United States Justin Basilico's profile →
Citations per field
00.5×6.3×
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Citations per year

Countries citing papers authored by Ilya Markov

Since Specialization
Citations

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

Fields of papers citing papers by Ilya Markov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ilya Markov. 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 Ilya Markov. The network helps show where Ilya Markov may publish in the future.

Co-authors

The 25 scholars most cited alongside Ilya Markov, 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 Ilya Markov Line = papers co-authored together Ilya Markov links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015111
2 201693
3 201584
4 201839
5 201928
6 202024
7 201523
8 201623
9 201618
10 201813
11
Overview of the NTCIR-12 IMine-2 Task.
201612
12 201211
13 20149
14 20146
15 20166
16 20186
17 20195
18 20214
19 20113
20 20072

About Ilya Markov

Ilya Markov is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research and Computer Networks and Communications, having authored 31 papers that have together received 533 indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (11 papers), Web Data Mining and Analysis (8 papers), Advanced Image and Video Retrieval Techniques (7 papers), Recommender Systems and Techniques (7 papers), Advanced Bandit Algorithms Research (6 papers), Image Retrieval and Classification Techniques (5 papers), Topic Modeling (5 papers) and Machine Learning and Algorithms (4 papers). The work is most often cited by research in Information Systems (366 citations), Computer Science Applications (53 citations), Management Science and Operations Research (113 citations), Artificial Intelligence (256 citations) and Computer Vision and Pattern Recognition (118 citations). Ilya Markov has collaborated with scholars based in Netherlands, Switzerland and Russia. Frequent co-authors include Maarten de Rijke, Aleksandr Chuklin, Alexey Borisov, Pavel Serdyukov, Rolf Jagerman, Fábio Crestani, Avi Arampatzis, Hongzhi Yin, Yifan Chen and Yang Wang. Their work appears in journals such as ACM Transactions on Information Systems, ACM SIGIR Forum, Journal of Machine Learning Research, Communications in computer and information science and UvA-DARE (University of Amsterdam).

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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