Fajri Koto

1.2k total citations
32 papers, 536 citations indexed

About

Fajri Koto is a scholar working on Artificial Intelligence, Language and Linguistics and Information Systems. According to data from OpenAlex, Fajri Koto has authored 32 papers receiving a total of 536 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 3 papers in Language and Linguistics and 2 papers in Information Systems. Recurrent topics in Fajri Koto's work include Topic Modeling (19 papers), Natural Language Processing Techniques (19 papers) and Sentiment Analysis and Opinion Mining (8 papers). Fajri Koto is often cited by papers focused on Topic Modeling (19 papers), Natural Language Processing Techniques (19 papers) and Sentiment Analysis and Opinion Mining (8 papers). Fajri Koto collaborates with scholars based in Australia, Indonesia and United Arab Emirates. Fajri Koto's co-authors include Timothy Baldwin, Jey Han Lau, Afshin Rahimi, Mirna Adriani, Samuel Cahyawijaya, Ade Romadhony, Alham Fikri Aji, Genta Indra Winata, Rahmad Mahendra and Sebastian Ruder and has published in prestigious journals such as Journal of Artificial Intelligence Research, Language Resources and Evaluation and Transactions of the Association for Computational Linguistics.

In The Last Decade

Fajri Koto

26 papers receiving 510 citations

Peers

Fajri Koto
Comparison fields: 5 of 69
  • Artificial Intelligence 458
  • Information Systems 141
  • Sociology and Political Science 48
  • Language and Linguistics 38
  • Computer Vision and Pattern Recognition 35
Replace Rahmad Mahendra with:
Rahmad Mahendra Indonesia
Daniel Hershcovich Denmark
El Moatez Billah Nagoudi Canada
Afshin Rahimi Australia
Renfen Hu China
Liviu P. Dinu Romania
Grégoire Winterstein France
Michael Pearce United States
Katia Lida Kermanidis Greece
Lilja Øvrelid Norway
Rahmad Mahendra Indonesia View profile →
Citations per field, relative to Fajri Koto
Fajri Koto · 1×
Citations per year, relative to Fajri Koto
Fajri Koto · 1×

Countries citing papers authored by Fajri Koto

Since Specialization
Citations

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

Fields of papers citing papers by Fajri Koto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fajri Koto

This figure shows the co-authorship network connecting the top 25 collaborators of Fajri Koto. A scholar is included among the top collaborators of Fajri Koto based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fajri Koto. Fajri Koto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 0
3 3
4 5
5 6
6 3
7 29
8 2
9 8
10 25
11 5
12 45
13 7
14 20
15 140
16 20
17
Improved Document Modelling with a Neural Discourse Parser
2
18 73
19
A Publicly Available Indonesian Corpora for Automatic Abstractive and Extractive Chat Summarization
14
20 10

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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