Jorma Laurikkala

1.8k total citations
39 papers, 708 citations indexed

About

Jorma Laurikkala is a scholar working on Artificial Intelligence, Information Systems and Statistics and Probability. According to data from OpenAlex, Jorma Laurikkala has authored 39 papers receiving a total of 708 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 9 papers in Information Systems and 6 papers in Statistics and Probability. Recurrent topics in Jorma Laurikkala's work include Imbalanced Data Classification Techniques (7 papers), Neural Networks and Applications (5 papers) and Advanced Statistical Methods and Models (4 papers). Jorma Laurikkala is often cited by papers focused on Imbalanced Data Classification Techniques (7 papers), Neural Networks and Applications (5 papers) and Advanced Statistical Methods and Models (4 papers). Jorma Laurikkala collaborates with scholars based in Finland, Sweden and Estonia. Jorma Laurikkala's co-authors include Martti Juhola, Erna Kentala, Kalervo Järvelin, Ilmari Pyykkö, Seppo Lammi, Henry Joutsijoki, Heikki Keskustalo, Ari Pirkola, Youming Zhang and Jyrki Rasku and has published in prestigious journals such as Annals of the New York Academy of Sciences, Information Sciences and Computer Methods and Programs in Biomedicine.

In The Last Decade

Jorma Laurikkala

38 papers receiving 664 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jorma Laurikkala Finland 13 376 136 61 61 60 39 708
Panayiotis Pintelas Greece 5 426 1.1× 109 0.8× 50 0.8× 38 0.6× 71 1.2× 7 702
David Martínez‐Rego Spain 13 345 0.9× 220 1.6× 50 0.8× 63 1.0× 109 1.8× 28 940
Leonard E. Trigg New Zealand 4 315 0.8× 193 1.4× 45 0.7× 87 1.4× 67 1.1× 5 683
Akın Özçift Türkiye 12 368 1.0× 129 0.9× 46 0.8× 63 1.0× 77 1.3× 22 762
George Almpanidis China 9 266 0.7× 134 1.0× 33 0.5× 80 1.3× 63 1.1× 14 607
Jesús Maillo Spain 8 325 0.9× 100 0.7× 25 0.4× 55 0.9× 81 1.4× 10 561
Diaa Salama AbdElminaam Egypt 15 440 1.2× 85 0.6× 57 0.9× 37 0.6× 132 2.2× 77 931
Nittaya Kerdprasop Thailand 12 266 0.7× 124 0.9× 22 0.4× 80 1.3× 75 1.3× 87 679
Shamila Nasreen Pakistan 6 377 1.0× 92 0.7× 70 1.1× 92 1.5× 161 2.7× 7 877

Countries citing papers authored by Jorma Laurikkala

Since Specialization
Citations

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

Fields of papers citing papers by Jorma Laurikkala

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jorma Laurikkala

This figure shows the co-authorship network connecting the top 25 collaborators of Jorma Laurikkala. A scholar is included among the top collaborators of Jorma Laurikkala 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 Jorma Laurikkala. Jorma Laurikkala 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
1.
Joutsijoki, Henry, et al.. (2017). Development of crime in England and Wales 1898–2001: Data mining using self-organising map. 1–8. 1 indexed citations
2.
Joutsijoki, Henry, et al.. (2017). GDP growth vs. criminal phenomena: data mining of Japan 1926–2013. AI & Society. 33(2). 261–274. 2 indexed citations
3.
Juhola, Martti, Kirsi Penttinen, Henry Joutsijoki, et al.. (2015). Signal analysis and classification methods for the calcium transient data of stem cell-derived cardiomyocytes. Computers in Biology and Medicine. 61. 1–7. 21 indexed citations
4.
Joutsijoki, Henry, et al.. (2015). On the influence of training data quality on text document classification using machine learning methods. 3(2). 143–143. 4 indexed citations
5.
Laurikkala, Jorma. (2012). Knowledge Discovery for Female Urinary Incontinence Expert System. Trepo - Institutional Repository of Tampere University. 1 indexed citations
6.
Laurikkala, Jorma, et al.. (2009). A study of the use of self‐organising maps in information retrieval. Journal of Documentation. 65(2). 304–322. 5 indexed citations
7.
Pirkola, Ari, et al.. (2008). Focused web crawling in the acquisition of comparable corpora. Information Retrieval. 11(5). 427–445. 18 indexed citations
8.
Laurikkala, Jorma, et al.. (2007). On principal component analysis, cosine and Euclidean measures in information retrieval. Information Sciences. 177(22). 4893–4905. 117 indexed citations
9.
Juhola, Martti, et al.. (2006). On the neural network classification of medical data and an endeavour to balance non-uniform data sets with artificial data extension. Computers in Biology and Medicine. 37(3). 388–397. 20 indexed citations
10.
Laurikkala, Jorma, et al.. (2006). A study on automatic creation of a comparable document collection in cross‐language information retrieval. Journal of Documentation. 62(3). 372–387. 1 indexed citations
11.
Juhola, Martti, et al.. (2006). Corpus‐based cross‐language information retrieval in retrieval of highly relevant documents. Journal of the American Society for Information Science and Technology. 58(3). 322–334. 10 indexed citations
12.
Laurikkala, Jorma, et al.. (2004). Stemming and lemmatization in the clustering of finnish text documents. 625–633. 127 indexed citations
13.
Kentala, Erna, et al.. (2001). Impact and Management of Confounding Values and Outliers in a Neurotologic Expert System. Annals of the New York Academy of Sciences. 942(1). 472–472. 1 indexed citations
14.
Laurikkala, Jorma, Erna Kentala, Martti Juhola, & Ilmari Pyykkö. (2001). A novel machine learning program applied to discover otological diagnoses. Scandinavian Audiology. 30(1). 100–102. 12 indexed citations
15.
Laurikkala, Jorma, Martti Juhola, Seppo Lammi, Jorma Penttinen, & Pauliina Aukee. (2001). Analysis of the imputed female urinary incontinence data for the evaluation of expert system parameters. Computers in Biology and Medicine. 31(4). 239–257. 15 indexed citations
16.
Kentala, Erna, et al.. (2001). Experiences of otoneurological expert system for vertigo. Scandinavian Audiology. 30(1). 90–91. 2 indexed citations
17.
Juhola, Martti, et al.. (2001). Application of artificial intelligence in audiology. Scandinavian Audiology. 30(1). 97–99. 3 indexed citations
18.
Laurikkala, Jorma, et al.. (2000). Usefulness of imputation for the analysis of incomplete otoneurologic data. International Journal of Medical Informatics. 58-59. 235–242. 21 indexed citations
19.
Laurikkala, Jorma & Martti Juhola. (1998). A genetic-based machine learning system to discover the diagnostic rules for female urinary incontinence. Computer Methods and Programs in Biomedicine. 55(3). 217–228. 21 indexed citations
20.
Laurikkala, Jorma, Martti Juhola, Jorma Penttinen, & Pauliina Aukee. (1997). Parameter evaluation of the differential diagnosis of female urinary incontinence for the construction of an expert system.. PubMed. 43 Pt B. 671–5. 1 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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