Tomas Eklund

720 total citations
31 papers, 438 citations indexed

About

Tomas Eklund is a scholar working on Artificial Intelligence, Management Science and Operations Research and Information Systems. According to data from OpenAlex, Tomas Eklund has authored 31 papers receiving a total of 438 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 11 papers in Management Science and Operations Research and 8 papers in Information Systems. Recurrent topics in Tomas Eklund's work include Stock Market Forecasting Methods (9 papers), Data Mining Algorithms and Applications (7 papers) and Big Data and Business Intelligence (5 papers). Tomas Eklund is often cited by papers focused on Stock Market Forecasting Methods (9 papers), Data Mining Algorithms and Applications (7 papers) and Big Data and Business Intelligence (5 papers). Tomas Eklund collaborates with scholars based in Finland and South Korea. Tomas Eklund's co-authors include Barbro Back, Hannu Vanharanta, Ari Visa, Aapo Länsiluoto, Jonas Karlsson, Peter Sarlin, Annukka Jokipii, Antti Arppe, Yoon‐Seok Chang and Jussi Kantola and has published in prestigious journals such as Information & Management, Journal of the Association for Information Systems and Neural Computing and Applications.

In The Last Decade

Tomas Eklund

29 papers receiving 397 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Tomas Eklund Finland	11	143	130	126	77	65	31	438
João Carvalho das Neves Portugal	9	152 1.1×	119 0.9×	182 1.4×	47 0.6×	69 1.1×	22	373
Enric Junqué de Fortuny Belgium	10	180 1.3×	112 0.9×	41 0.3×	62 0.8×	66 1.0×	15	527
Markku Heikkilä Finland	8	93 0.7×	131 1.0×	86 0.7×	90 1.2×	77 1.2×	21	368
Utkarsh Goel India	9	50 0.3×	50 0.4×	136 1.1×	58 0.8×	78 1.2×	29	415
Ram S. Sriram United States	15	150 1.0×	99 0.8×	344 2.7×	137 1.8×	46 0.7×	34	615
Ruibin Geng China	5	156 1.1×	92 0.7×	268 2.1×	28 0.4×	49 0.8×	10	519
Roger Stein United States	6	222 1.6×	65 0.5×	66 0.5×	78 1.0×	47 0.7×	13	489
Chin‐Shien Lin Taiwan	9	68 0.5×	76 0.6×	105 0.8×	49 0.6×	47 0.7×	18	554
Dimitris N. Chorafas United States	11	70 0.5×	56 0.4×	103 0.8×	88 1.1×	91 1.4×	119	532
An‐An Chiu Taiwan	8	116 0.8×	68 0.5×	144 1.1×	74 1.0×	23 0.4×	18	345

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-authorship network of co-authors of Tomas Eklund

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

All Works

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20 of 20 papers shown

Sarlin, Peter, et al.. (2013). Visual Data-Driven Profiling of Green Consumers. 291–298. 2 indexed citations

Sarlin, Peter, et al.. (2013). Combining visual customer segmentation and response modeling. Neural Computing and Applications. 25(1). 123–134. 17 indexed citations

Liu, Hongyan, et al.. (2012). From Smart Meter Data to Pricing Intelligence -- Visual Data Mining towards Real-Time BI. Journal of the Association for Information Systems. 120. 506–23. 1 indexed citations

Sarlin, Peter, et al.. (2012). Combining Visual Customer Segmentation and Response Modeling.. Journal of the Association for Information Systems. 143. 3 indexed citations

Sarlin, Peter, et al.. (2012). A FRAMEWORK FOR STATE TRANSITIONS ON THE SELF‐ORGANIZING MAP: SOME TEMPORAL FINANCIAL APPLICATIONS. Intelligent systems in accounting, finance and management. 19(3). 189–203. 9 indexed citations

Sarlin, Peter, et al.. (2012). Temporal Customer Segmentation Using the Self-organizing Time Map. 6. 234–240. 4 indexed citations

Eklund, Tomas, et al.. (2011). Customer Feedback Analysis using Collocations. Journal of the Association for Information Systems. 1 indexed citations

Eklund, Tomas, et al.. (2011). Customer portfolio analysis using the SOM. International Journal of Business Information Systems. 8(4). 396–396. 21 indexed citations

Jokipii, Annukka, Aapo Länsiluoto, & Tomas Eklund. (2011). A clustering and visualisation approach to the analysis of internal control structures. International Journal of Accounting Auditing and Performance Evaluation. 7(3). 151–151. 1 indexed citations

10.

Länsiluoto, Aapo & Tomas Eklund. (2008). On the suitability of the self‐organizing map for analysis of the macro and firm level competitive environment. Benchmarking An International Journal. 15(4). 402–419. 10 indexed citations

11.

Eklund, Tomas, Barbro Back, Hannu Vanharanta, & Ari Visa. (2008). A Face Validation of a SOM-Based Financial Benchmarking Model. Journal of Emerging Technologies in Accounting. 5(1). 109–127. 10 indexed citations

12.

Eklund, Tomas, et al.. (2004). Combining data and text mining techniques for analysing financial reports: Research Articles. Intelligent Systems in Accounting Finance & Management. 12(1). 29–41. 7 indexed citations

13.

Arppe, Antti, et al.. (2004). The language of quarterly reports as an indicator of change in the company’s financial status. Information & Management. 42(4). 561–574. 43 indexed citations

14.

Eklund, Tomas, et al.. (2003). A two-level approach to making class predictions. 43. 9 pp.–9 pp.. 5 indexed citations

15.

Eklund, Tomas, Barbro Back, Hannu Vanharanta, & Ari Visa. (2003). Using the Self-Organizing Map as a Visualization Tool in Financial Benchmarking. Information Visualization. 2(3). 171–181. 41 indexed citations

16.

Eklund, Tomas, et al.. (2002). Combining Data and Text Mining Techniques for Analyzing Financial Reports. 17 indexed citations

17.

Eklund, Tomas, Barbro Back, Hannu Vanharanta, & Ari Visa. (2002). ASSESSING THE FEASIBILITY OF SELF-ORGANIZING MAPS FOR DATA MINING FINANCIAL INFORMATION. Journal of the Association for Information Systems. 528–540. 22 indexed citations

18.

Eklund, Tomas, et al.. (2002). A Framework for Predictive Data Mining in the Telecommunications Sector.. 14(7). 38–46. 1 indexed citations

19.

Eklund, Tomas, et al.. (2001). Benchmarking Global Pulp and Paper Companies Using Self-Organizing Maps. Åbo Akademi University Research Portal. 2 indexed citations

20.

Eklund, Tomas, Barbro Back, Hannu Vanharanta, & Ari Visa. (2001). Benchmarking International Pulp and Paper Companies Using Self-Organizing Maps. 5 indexed citations

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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