Adam Jatowt

5.3k citations
199 papers · 2.2k indexed · 1 hit paper · h-index 21
Topics
Topic Modeling (74 papers)Advanced Text Analysis Techniques (53 papers)Natural Language Processing Techniques (44 papers)
Journals
SHILAP Revista de lepidopterologíaPLoS ONEIEEE Access
Partner nations
JapanAustriaChina

In The Last Decade

Adam Jatowt

179 papers receiving 2.0k citations

Hit Papers

YAKE! Keyword extraction from single documents using mult...20192026202120232019100200300

Peers

Adam Jatowt
Comparison fields: 5 of 132
  • Artificial Intelligence 1.4k
  • Information Systems 703
  • Computer Vision and Pattern Recognition 275
  • Sociology and Political Science 207
  • Signal Processing 198
Replace Adriano Veloso with:
Adriano Veloso Brazil
Giovanni Semeraro Italy
Heiko Paulheim Germany
Geert‐Jan Houben Netherlands
Petr Sojka Czechia
Fábio Crestani Switzerland
Rion Snow United States
Matthew Lease United States
Jie Yang Netherlands
Martine De Cock Belgium
Adam Jatowt relative to Adriano Veloso Brazil Adriano Veloso's profile →
Citations per field
00.5×
Adriano Veloso · 1×
Citations per year

Countries citing papers authored by Adam Jatowt

Since Specialization
Citations

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

Fields of papers citing papers by Adam Jatowt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adam Jatowt

This figure shows the co-authorship network connecting the top 25 collaborators of Adam Jatowt. A scholar is included among the top collaborators of Adam Jatowt 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 Adam Jatowt. Adam Jatowt 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
#WorkIndexed citations
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Understanding Characteristics of Biased Sentences in News Articles.
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Proceedings of the 3rd HistoInformatics Workshop on Computational History (HistoInformatics 2016) co-located with the Digital Humanities 2016 conference (DH 2016)
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Overview of NTCIR-11 Temporal Information Access (Temporalia) Task
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About Adam Jatowt

Adam Jatowt is a scholar working on Artificial Intelligence, Information Systems and Communication, having authored 199 papers that have together received 2.2k indexed citations. Recurring topics across this work include Topic Modeling (74 papers), Advanced Text Analysis Techniques (53 papers) and Natural Language Processing Techniques (44 papers). The work is most often cited by research in Artificial Intelligence (1.4k citations), Information Systems (703 citations) and Signal Processing (198 citations). Adam Jatowt has collaborated with scholars based in Japan, Austria and China. Frequent co-authors include Katsumi Tanaka, Ricardo Campos, Alí­pio Jorge, Arian Pasquali, Vítor Mangaravite, Célia Nunes, Yukiko Kawai, Michael Färber, Ching‐man Au Yeung and Antoine Doucet. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Access.

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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