BACKGROUND: Research confirms that physical activity (PA) is irreplaceable in a healthy and physically active lifestyle. One of the key research questions is what the optimal level of everyday PA for health is and how it should be quantified and interpreted. Formal concept analysis is one possible way of how to assess and describe the level of PA as related to personal data. OBJECTIVE: The main goal of this study was to introduce the method of Formal Concept Analysis (FCA) using data from the ANEWS questionnaire and data from the objective monitoring of a number of steps using the YAMAX SW-701 pedometer. A further aim was to adopt the most appropriate method within the FCA. METHODS: A random sample of 273 males aged 18-69 from selected regional centers participated in the study. RESULTS: The example of daily steps allows for the demonstration of how important it is to select a scale in FCA data analysis. It is better to use an ordinal scale for the daily number of steps (in our example); because, in so doing, we create the attributes that can be ordered (a lower number of steps is also insufficient). CONCLUSIONS: A rough scale produces easier lattice with the general scope of the observed attributes. The smoothing of the scale produces more difficult lattice and makes for more difficult analyses, but gives more detailed results. FCA requires more expertise from a researcher than do "classical" testing statistics, but gives us deeper insight into the examination of the problem.
G. Stumme. Semantic Interoperability and Integration, 04391, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany, (2005)$<$http://drops.dagstuhl.de/opus/volltexte/2005/49$>$
date of citation: 2005-01-01.
P. Becker. Concept Lattices: Proceedings of the Second International Conference on Formal Concept Analysis, ICFCA 2004, Seite 96-103. Berlin, Springer-Verlag, (2004)
B. Ganter, und C. Meschke. Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, 12th International Conference, RSFDGrC 2009, Delhi, India, December 15-18, 2009. Proceedings, Volume 5908 von Lecture Notes in Computer Science, Seite 117-126. (2009)
D. Jurkevicius, und O. Vasilecas. CompSysTech '09: Proceedings of the International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing, Seite 1--5. New York, NY, USA, ACM, (2009)
W. Chen, Q. Yang, L. Zhu, und B. Wen. ICICTA '09: Proceedings of the 2009 Second International Conference on Intelligent Computation Technology and Automation, Seite 764--767. Washington, DC, USA, IEEE Computer Society, (2009)
P. Fang, und S. Zheng. KAM '09: Proceedings of the 2009 Second International Symposium on Knowledge Acquisition and Modeling, Seite 352--355. Washington, DC, USA, IEEE Computer Society, (2009)
F. Baader, B. Ganter, B.Sertkaya, und U. Sattler. Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI'07), Seite 230--235. (2007)
C. Zhou. WCSE '09: Proceedings of the 2009 WRI World Congress on Software Engineering, Seite 155--159. Washington, DC, USA, IEEE Computer Society, (2009)
M. Yuan, W. Li, und L. Zhangang. WCSE '09: Proceedings of the 2009 WRI World Congress on Software Engineering, Seite 94--98. Washington, DC, USA, IEEE Computer Society, (2009)