Eric Malmi

1.6k citations
26 papers · 304 · h-index 10

Impact in

    • Natural Language Processing Techniques
    • Topic Modeling
    • Text Readability and Simplification
    • Advanced Graph Neural Networks
    • Advanced Text Analysis Techniques
    • Human Mobility and Location-Based Analysis

Papers in

Eric Malmi

25 papers receiving 277 citations

Peers

Eric Malmi
Comparison fields: 5 of 59
  • Artificial Intelligence 225
  • Transportation 22
  • Computer Vision and Pattern Recognition 37
  • Information Systems 40
  • Computational Mathematics 1
Replace Dimitrios Kotzias with:
Dimitrios Kotzias United States
Steven Van Canneyt Belgium
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Lynda Tamine France
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Joachim Daiber Netherlands
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Citations per field
00.5×3.8×
Dimitrios Kotzias · 1×
Citations per year

Countries citing papers authored by Eric Malmi

Since Specialization
Citations

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

Fields of papers citing papers by Eric Malmi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201977
2 202348
3 201932
4 201220
5 202219
6 202217
7
201916
8 201714
9 201210
10
Automatic prediction of discourse connectives
20189
11 20178
12 20156
13 20135
14 20204
15 20144
16 20203
17 20182
18
Warfare Simulation and Technology Forecasting in Support of Military Decision Making
20112
19 20172
20 20171

About Eric Malmi

Eric Malmi is a scholar working on Artificial Intelligence, Information Systems, Transportation, Statistical and Nonlinear Physics and Signal Processing, having authored 26 papers that have together received 304 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Topic Modeling (9 papers), Text Readability and Simplification (5 papers), Human Mobility and Location-Based Analysis (4 papers), Web Data Mining and Analysis (3 papers), Data-Driven Disease Surveillance (3 papers), Complex Network Analysis Techniques (3 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (225 citations), Transportation (22 citations), Computer Vision and Pattern Recognition (37 citations), Information Systems (40 citations) and Computational Mathematics (1 citation). Eric Malmi has collaborated with scholars based in Finland, United States and Switzerland. Frequent co-authors include Aliaksei Severyn, Sebastian Krause, Daniil Mirylenka, Jonathan Mallinson, Jakub Adámek, Sascha Rothe, Aristides Gionis, Daniel Gática-Pérez, Trinh Minh Tri and Claudia Wagner. Their work appears in journals such as Data Mining and Knowledge Discovery, EPJ Data Science, International Journal of Modern Physics A, The Journal of Defense Modeling and Simulation Applications Methodology Technology and Aaltodoc (Aalto University).

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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