Tomas Eklund

29 papers receiving 397 citations

Peers

Tomas Eklund
Comparison fields: 5 of 72
  • Accounting 126
  • Management Science and Operations Research 130
  • Management Information Systems 77
  • Marketing 57
  • Artificial Intelligence 143
Replace João Carvalho das Neves with:
João Carvalho das Neves Portugal
Utkarsh Goel India
Markku Heikkilä Finland
Enric Junqué de Fortuny Belgium
Chin‐Shien Lin Taiwan
Ruibin Geng China
Roger Stein United States
Ram S. Sriram United States
Dimitris N. Chorafas United States
Anis El Ammari Tunisia
Tomas Eklund relative to João Carvalho das Neves Portugal João Carvalho das Neves's profile →
Citations per field
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João Carvalho das Neves · 1×
Citations per year

Countries citing papers authored by Tomas Eklund

Since Specialization
Citations

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

Fields of papers citing papers by Tomas Eklund

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Tomas Eklund, 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 Tomas Eklund Line = papers co-authored together Tomas Eklund links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004104
2 200443
3 201542
4 200341
5
ASSESSING THE FEASIBILITY OF SELF-ORGANIZING MAPS FOR DATA MINING FINANCIAL INFORMATION
200222
6 201121
7 200519
8
Combining Data and Text Mining Techniques for Analyzing Financial Reports
200217
9 201317
10 200914
11 201011
12 200810
13 200810
14 200410
15 20129
16
Combining data and text mining techniques for analysing financial reports: Research Articles
20047
17 20137
18 20035
19
Benchmarking International Pulp and Paper Companies Using Self-Organizing Maps
20015
20 20124

About Tomas Eklund

Tomas Eklund is a scholar working on Artificial Intelligence, Management Science and Operations Research, Information Systems, Management Information Systems and Marketing, having authored 31 papers that have together received 438 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (9 papers), Data Mining Algorithms and Applications (7 papers), Neural Networks and Applications (5 papers), Big Data and Business Intelligence (5 papers), Advanced Text Analysis Techniques (4 papers), Complex Systems and Time Series Analysis (4 papers), Time Series Analysis and Forecasting (4 papers) and Customer churn and segmentation (4 papers). The work is most often cited by research in Accounting (126 citations), Management Science and Operations Research (130 citations), Management Information Systems (77 citations), Marketing (57 citations) and Artificial Intelligence (143 citations). Tomas Eklund has collaborated with scholars based in Finland and South Korea. Frequent co-authors include Barbro Back, Hannu Vanharanta, Ari Visa, Aapo Länsiluoto, Jonas Karlsson, Annukka Jokipii, Peter Sarlin, Antti Arppe, Yoon‐Seok Chang and Jussi Kantola. Their work appears in journals such as Journal of the Association for Information Systems, Intelligent systems in accounting, finance and management, Information & Management, Benchmarking An International Journal and Managerial Auditing Journal.

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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