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ANALYSIS OF ANNUAL REPORTS BY ADVANCED NEURAL NETWORK METHODS

Professor: Ari Visa

Abstract

The goal of the project was to test if it is possible to find any correlation between the text part and the corresponding economical figures of annual reports. The problem is complicated because depending on the report there is more or less correlation. There might also be some time delays between the proclamation and the actual figures. The team was created by experts in the economics, in the management, and in the neurocomputing. The problem was studied by four hypothesises. As a reference time series of the economical figures of the actual companies were considered. The analysed statements of the annual reports were compared with the behaviour of the time series. As an answer to the text interpretation problem a new technology based on multilevel hierarchies of Self-Organizing Feature Maps and on smart encoding of words was proposed. The results are interesting and promising. They are supporting the hypothesises but one should be careful with the final conclusions. However, in our second test case, where we analysed fault reports in electrical power industry, the results were interesting in such a way that the work will continue at least in that field.

Results

As an answer to the text interpretation problem a new technology was proposed. The Technology is based on multilevel hierarchies of Self-Organizing Feature Maps and on smart encoding of words.The encoding of the word is language independent. The levels of the hierarchy are word, sentence, and paragraph maps. Our experiments with text documents (annual reports) show that with text documents it is possible to achieve similar results as with analysis of economical figures. Besides that it is possible both to find similar documents and to separate between different types of documents. This is also true considering paragraphs within a document. The technology might find some applications in the field of intellectual property rights concerning text documents. In our second test case, where we analysed fault reports in electrical power industry, the results were promising. It seems that the work will continue with more specific applications.

Project information

The research work was done in Department of Information Science at Lappeenranta University of Technology and in Laboratory of Information Systems at Åbo Akademi University, Finland during 1.March 1998 - 31. December 1999. The budget of this two years project was roughly 1.2 MFIM, and the amount of work was about 44 person months. The work was carried out in close co-operation with the following industrial companies:

Ramse Consulting Oy
Teollisuuden Voima Oy

The project manager was professor Ari Visa.

Publications

The publishing of the results is just going on. To date four papers have been published and four papers have been submitted. The information about the future publications can be found from this web page.
The following list of publications consists of those publications that have been published or are accepted to be published.

Refereed International Conference Papers

Back, B., Vanharanta, H., Toivonen, J., Visa, A., Knowledge Discovery In Analyzing Texts In Annual Reports, IFORS SPC-9 Conference, 25-27 April, Turku, Finland, pp 9-11,1999.
Back, B., Vanharanta, H., Toivonen, V., Visa, A., Toward Computer Aided Analysis of Text in Annual Reports, in Proc. of 2nd European Conference on Accounting Information Systems (CD-ROM), Bordeaux, France, May 3-4, p 8, 1999.
Visa, A., Toivanen, J., Back, B., Vanharanta, H.,. Towards Text Understanding - Comparison of Text Documents by Sentence Map, in Proceedings of EUFIT 99 (CD_ROM), Aachen, Germany, September 13-16, p.6, 1999.
Ari Visa, Jarmo Toivonen, Barbro Back, Hannu Vanharanta, Knowledge Discovery From Text Documents Based On Context Maps, Proceedings of the Thirty-third Annual Hawai'I International Conference on System Sciences (HICSS), Maui, Hawai'I, January 4-7, p. 8, CD-ROM, 2000.
Ari Visa, Jarmo Toivonen, Barbro Back, Hannu Vanharanta, Toward text understanding: characterization and classification of text documents by word map. in Proceedings of SPIE's International Symposium on Optical Engineering in Aerospace Sensing, Vol 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, SPIE AeroSense 2000, 24-25 April, Orlando, FL, USA, pp. 299-306, 2000.
Ari Visa, Jarmo Toivonen, Barbro Back, Hannu Vanharanta, A New Methodology for Knowledge Retrieval from Text Documents, (Eds).Leena Yliniemi, Esko Juuso, Proceedings of TOOLMET2000: Symposium on Tool Environments and Development Methods for Intelligent Systems, April 13-14, 2000, Oulu, pp. 147 -152. 2000, ISBN951-42-5595-x.
Kristoffer Öström, Barbro Back, Hannu Vanharanta, Ari Visa, Descriptive Statistics on Companies in the Forest Products Industry, Turku Centre for Computer Science TUCS Technical Report No 330, February 2000, ISBN 952-12-0614-4

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