Comparing numerical data and text information from annual reports using self-organizing maps |
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| Institution: | 1. Department of Orthopedic Surgery, The Spine Hospital at New York Presbyterian Hospital, Columbia University, 5141 Broadway, 3 Field west-022, New York, NY 10034, United States;2. University of Toronto and Toronto Western Hospital, 399 Bathurst St, Toronto, ON M5T 2S8, Canada;3. University of Virginia, 1215 Lee St, Charlottesville, VA 22908, United States;4. Queen Mary Hospital, The University of Hong Kong, 102 Pok Fu Lam Road, Hong Kong;5. Norton Leatherman Spine Center, 210 E Gray St #900, Louisville, KY 40202, United States;6. The CORE Institute, 14520 W Granite Valley Dr, Sun City West, AZ 85375, United States;7. Hospital for Special Surgery, 535 East 70th Street, New York, NY 10021, United States;8. The FOCOS Hospital, 8 Teshie Street, Pantang West, Ghana;9. Johns Hopkins University, 3101 Wyman Park Dr., Baltimore, MD 21211, United States;10. University of California San Francisco, 505 Parnassus Ave. San Francisco, CA 94143, United States;11. Affiliated Drum Tower Hospital of Nanjing University Medical School, 101Longmian Avenue, Jiangning District, Nanjing 211166, P.R. China;12. Hamamatsu University School of Medicine, 1 Chome-20-1 Handayama, Hamamatsu, Shizuoka Prefecture 431-3192, Japan;13. Rigshospitalet, National University of Denmark, Blegdamsvej 9, 2100 København, Denmark;14. Department of Orthopedic Surgery, Texas Children’ Hospital and Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, United States;15. University Hospital, Queen''s Medical Centre, Derby Road, Nottingham, NG7 2UH, England;p. Hospital Universitari Vall d''Hebron, Passeig de la Vall d''Hebron, 119-129, 08035 Barcelona, Spain;1. Department of Geology and Geoenvironment, National and Kapodistrian University of Athens, Panepistimiopolis Zographou, 15784 Athens, Greece;2. Edafomichaniki S.A., Em. Papadaki 19, 141 21, N., Iraklion, Athens, Greece |
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| Abstract: | More and more companies provide their accounting information in electronic form today. The accounting information in electronic form can be found in large commercial databases or on the web. This information is of great interest for different stakeholders, i.e., stockholders, creditors, auditors, financial analysts, and management. For the stakeholders it is important to be able to extract both quantitative and qualitative information concerning the companies they are interested in. The annual reports contain information both in numerical and symbolic form. So far, only the numerical information has been analyzed with help of computers. However, technology has evolved and in particular neural networks in the form of self-organizing maps (SOMs) provide a new tool for analyzing also text information. In this paper, we compare results on quantitative data with results on qualitative data from annual reports. We use smart encoding, SOMs, and document histograms for comparing the performance of forest companies worldwide. Firstly, we cluster the companies according to, on the one hand, quantitative information, and on the other hand, qualitative information. Secondly, we compare the results produced by the clustering methods. Our results of the comparison show that there is a difference between the results. |
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