Abstract
In this paper an original approach to analytical decision making support based on on-line analytical processing of multidimensional data is suggested. According to Dr. Codd’s rules, the effectiveness of data analysis significantly depends on the data accessibility and transparency of an analytical model of domain. The method of constructing a conceptual OLAP-model as an integral analytical model of the domain is proposed. The method is illustrated by the example of the scientific activities domain. The integral analytical model includes all possible combinations of analyzed objects and gives them the opportunity to be manipulated ad-hoc. The suggested method consists in a formal concept analysis of measures and dimensions based on an expert knowledge about the structure of analyzing objects and their comparability. As a result, conceptual OLAP-model is represented as a concept lattice of multidimensional cubes. Concept lattice features allow the decision maker to discover the nonstandard analytical dependencies on the set of all actual measures and dimensions of the scientific activities domain. Conceptual OLAP-model implementation allows user makes better decisions based on on-line analytical processing of the scientific activity indicators.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gorelov, B.A., Gorelov, B.B.: Model data constructing for on-line analitical processing of the financial information of the University. J. University Management 4(23), 33–46 (2002)
Nozhenkova, L.F., Shaidurov, V.V.: OLAP technologies of on-line analytical support of administration. J. Information Technology and Computing Systems 2, 15–27 (2010)
Palaniappan, S., Ling, C.: Clinical Decision Support Using OLAP With Data Mining. International Journal of Computer Science and Network Security 8(9), 290–296 (2008)
Javed, A., Shaikh, M., Bhatti, B.: Conceptual Model for Decision Support System Based Business Intelligence OLAP Tool for Universities in Context of E-Learning. In: World Congress on Engineering and Computer Science, pp. 826–830 (2008)
Vasilecas, O., Smaizys, A.: Business rule based data analysis for decision support and automation. In: International Conference on Computer Systems and Technologies, vol. II (2006)
Bojarsky N.A., Shovkun A.V.: Analytical part of information-analytical sysytem constracting by Oracle OLAP Option и BI Beans, Oracle Magazine RE (2004), http://www.interface.ru/home.asp?artId=9604
Lee, J., Mazzoleni, P., Sairamesh, J., Touma, M.: System and method for planning and generating queries for multi-dimensional analysis using domain models and data federation. United States Patent: US 2008/7337170 B2
Korobko, A., Penkova, T.: OLAP-modeling of municipal procurement automation support problem. In: International Conference on Conceptual Structures, pp. 87–91 (2009)
Korobko, A., Penkova, T.: On-line analytical processing based on Formal concept analysis. J. Procedia Computer Science 1(1), 2305–2311 (2010)
Codd, E.F.: Providing OLAP to user-analysts: An IT mandate. Codd and Associates (1993)
Gray, J., Bosworth, A., Layman, A., Priahesh, H.: Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals. In: 12 th International Conference on Data Engineering, pp. 152–159. IEEE (1995)
Kedrov, S., Kuznetsov, S.: Study of Groups of Web Users with Methods Based on Formal Concept Analysis and Data Mining. J. Business-informatics (1), 45–51 (2007)
Ganter, B., Wille, R.: Formal Concept Analysis: mathematical Foundations. Springer, Heidelberg (1999)
Wille, R.: Restructuring Lattice Theory: an approach based on hierarchies of concept, pp. 445–470. Reidel, Dordrecht (1982)
Birkhoff, G.: Lattice theory, 568 p. Nauka, Moscow (1984)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Penkova, T., Korobko, A. (2013). Constructing the Integral OLAP-Model for Scientific Activities Based on FCA. In: Graña, M., Toro, C., Howlett, R.J., Jain, L.C. (eds) Knowledge Engineering, Machine Learning and Lattice Computing with Applications. KES 2012. Lecture Notes in Computer Science(), vol 7828. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37343-5_17
Download citation
DOI: https://doi.org/10.1007/978-3-642-37343-5_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37342-8
Online ISBN: 978-3-642-37343-5
eBook Packages: Computer ScienceComputer Science (R0)