Mikael Kågebäck

420 citations
6 papers · 149 indexed · h-index 5
Topics
Natural Language Processing Techniques (4 papers)Advanced Text Analysis Techniques (3 papers)Topic Modeling (3 papers)
Journals
PLoS ONEInternational Journal on Digital LibrariesChalmers Publication Library (Chalmers University of Technology)
Partner nations
SwedenGermany

In The Last Decade

Mikael Kågebäck

6 papers receiving 136 citations

Peers

Mikael Kågebäck
Comparison fields: 5 of 32
  • Artificial Intelligence 134
  • Information Systems 14
  • Computer Vision and Pattern Recognition 10
  • Molecular Biology 8
  • Cultural Studies 5
Replace Verginica Barbu Mititelu with:
Verginica Barbu Mititelu Romania
Amalia Todiraşcu France
Igor Boguslavsky Russia
Ioannis P. Klapaftis United Kingdom
Dima Taji United States
Alexander Erdmann United States
Behrang QasemiZadeh Germany
Daniela Gerz United Kingdom
Špela Vintar Slovenia
Miryam de Lhoneux Sweden
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Citations per field
00.5×
Verginica Barbu Mititelu · 1×
Citations per year

Countries citing papers authored by Mikael Kågebäck

Since Specialization
Citations

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

Fields of papers citing papers by Mikael Kågebäck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mikael Kågebäck

This figure shows the co-authorship network connecting the top 25 collaborators of Mikael Kågebäck. A scholar is included among the top collaborators of Mikael Kågebäck 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 Mikael Kågebäck. Mikael Kågebäck is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

6 of 6 papers shown
#WorkIndexed citations
1 8
2
Disentangled activations in deep networks
1
3
Extractive summarization by aggregating multiple similarities
10
4 10
5 8
6 112

About Mikael Kågebäck

Mikael Kågebäck is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Experimental and Cognitive Psychology, having authored 6 papers that have together received 149 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (4 papers), Advanced Text Analysis Techniques (3 papers) and Topic Modeling (3 papers). The work is most often cited by research in Artificial Intelligence (134 citations), Information Systems (14 citations) and Cultural Studies (5 citations). Mikael Kågebäck has collaborated with scholars based in Sweden and Germany. Frequent co-authors include Devdatt Dubhashi, Olof Mogren, Nina Tahmasebi, Fredrik Johansson, Richard Johansson, Emil Carlsson, Asad Sayeed, Thomas Risse, Lars Borin and Markus Forsberg. Their work appears in journals such as PLoS ONE, International Journal on Digital Libraries and Chalmers Publication Library (Chalmers University of Technology).

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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