Silja Huttunen

621 citations
12 papers · 412 indexed · h-index 8
Topics
Web Data Mining and Analysis (5 papers)Topic Modeling (5 papers)Biomedical Text Mining and Ontologies (4 papers)
Journals
Journal of Biomedical InformaticsLanguage Resources and EvaluationJoint Research Centre (European Commission)

In The Last Decade

Silja Huttunen

12 papers receiving 358 citations

Peers

Silja Huttunen
Comparison fields: 5 of 42
  • Artificial Intelligence 318
  • Information Systems 146
  • Molecular Biology 73
  • Epidemiology 60
  • Management Science and Operations Research 38
Replace Andrew Borthwick with:
Andrew Borthwick United States
Mohamed Yahya Germany
Stijn De Saeger Japan
Claude Chrisment France
Egoitz Laparra Spain
Rongjian Lan United States
Sumio Fujita Japan
Raquel Martínez Spain
Seung-won Hwang South Korea
Yasuhide Miura Japan
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Citations per field
00.5×
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Citations per year

Countries citing papers authored by Silja Huttunen

Since Specialization
Citations

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

Fields of papers citing papers by Silja Huttunen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Silja Huttunen

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

All Works

12 of 12 papers shown
#WorkIndexed citations
1
Event representation across genre
7
2
Relevance Prediction in Information Extraction using Discourse and Lexical Features
2
3 13
4 3
5 3
6 13
7 18
8 70
9 18
10 40
11 169
12 56

About Silja Huttunen

Silja Huttunen is a scholar working on Artificial Intelligence, Information Systems and Epidemiology, having authored 12 papers that have together received 412 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (5 papers), Topic Modeling (5 papers) and Biomedical Text Mining and Ontologies (4 papers). The work is most often cited by research in Artificial Intelligence (318 citations), Information Systems (146 citations) and Management Science and Operations Research (38 citations). Silja Huttunen has collaborated with scholars based in Finland, United States and Italy. Frequent co-authors include Roman Yangarber, Ralph Grishman, Pasi Tapanainen, Arto Vihavainen, Матти Вуоринен, Lidia Pivovarova, Vanni Zavarella, Jakub Piskorski and Martin Atkinson. Their work appears in journals such as Journal of Biomedical Informatics, Language Resources and Evaluation and Joint Research Centre (European Commission).

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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