Abstract
The most difficult and time consuming activity to perform during view integration is to find correspondences between different view specifications. Such correspondences may be the source for conflicts when integrating the views and thus must be detected and resolved. A manual inspection of the class definitions in each view and a comparison with each class definition in the other views may result in an almost endless process. To support a designer we propose a computerized tool to extract the semantics from view definitions, to transform them into a unique vector representation of each class, and to use the class vectors to train a neural network in order to determine categories of classes. The output of the tool is a ‘first guess’ which concepts in views may be overlapping or which concepts do not overlap at all. This may be of tremendous value because the designers are relieved from manual inspection of all the classes and can direct their focus on classes grouped into the same category.
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References
M. Bouzeghoub, I. Comyn-Wattiau. View Integration by Semantic Unification and Transformation of Data Structures. Proc. 9th Int. Conf. on the Entity-Relationship Approach, North Holland, 1990.
C. Batini, M. Lenzerini, S. B. Navathe. A Comparative Analysis of Methodologies for Database Schema Integration. ACM Computing Surveys, Vol. 18, No 4, pp. 323–364, 1986.
J. Biskup, B. Convent. A Formal View Integration Method. Proc. ACM Int. Conf. on Managment of Data (Sigmod), Washington, DC, 1986.
W. Bright, A Hurson. A Taxonomy and Current Issues in Multidatabase Systems. IEEE Computer, Vol 24, No. 10, 1990.
P. P. Chen. The Entity-Relationship Model — Toward a Unified View of Data. ACM Trans. on Database Systems (ToDS), Vol. 1, No. 1, pp. 9–36, 1976.
C. Date. An Introduction to Database Systems. Addison-Wesley, 1991.
P. Fankhauser, M. Kracker, E. Neuhold. Semantic vs. Structural Resemblance of Classes. ACM Sigmod Record, Vol. 20, No. 4, Dec. 1991.
P. Johannesson. A Logical Basis for Schema Integration. Proc. 3rd Int. Workshop on Research Issues in Data Engineering (RIDE), IEEE Comp. Society Press, 1993.
P. Johannesson. Using Conceptual Graph Theory to Support Schema Integration. Proc. 12th Int. Conf. on the Entity-Relationship Approach, Springer Verlag, LNCS 823, 1994. (R. Elmasri, V. Kouramajian, B. Thalheim, Eds.).
T. Kohonen. The Self-Organizing Map. Proceedings of the IEEE 78(9). 1990.
T. Kohonen. Self-Organizing Maps. Berlin: Springer-Verlag. 1995.
J. A. Larson, S. B. Navathe, R. Elmasri. A Theory of Attribute Equivalence in Databases with Applications to Schema Integration. IEEE Trans. on Software Engineering (ToSE). Vol. 15, No. 4, pp. 449–463, 1989.
W.-S. Li, C. Clifton. Semantic Integration in Heterogeneous Databases Using Neural Networks. Proc. 20th VLDB Conference, Santiago, Chile, 1994.
P. Mehra and B. J. Wah (Eds.). Artificial Neural Networks: Concepts and Theory. Los Alamitos, CA: IEEE Computer Society Press. 1992.
A. Motro. Superviews: Virtual Integration of Multiple Databases. IEEE Trans. on Software Engineering (ToSE). Vol. 13, No. 7, pp. 785–798, 1987.
S. B. Navathe, S. G. Gadgil. A Methodology for View Integration in Logical Database Design. Proc. 8th Int. Conf. on the Entity-Relationship Approach, North Holland, 1982.
J. Rumbaugh, et al. Object-Oriented Modeling and Design. Prentice Hall, 1991.
W. W. Song, P. Johannesson, J. Bubenko. Semantic Similarity Relations in Schema Integration. Proc. 11th Int. Conf. on the Entity-Relationship Approach, Springer Verlag, LNCS 645, 1992. (G. Pernul, A M. Tjoa, Eds.).
S. Spaccapietra, C. Parant, Y. Dupont. Model Independent Assertions for Integration of Heterogeneous Schemes. The VLDB Journal, Vol. 1, No. 2, pp. 81–126, 1992.
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Ellmer, E., Huemer, C., Merk, D., Pernu, G. (1995). Neural network technology to support view integration. In: Papazoglou, M.P. (eds) OOER '95: Object-Oriented and Entity-Relationship Modeling. ER 1995. Lecture Notes in Computer Science, vol 1021. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020531
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DOI: https://doi.org/10.1007/BFb0020531
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