Abstract
Relationships are an essential part of the design of a database because they capture associations between things. Comparing and integrating relationships from heterogeneous databases is a difficult problem, partly because of the nature of the relationship verb phrases. This research proposes a multi-layered approach to classifying the semantics of relationship verb phrases to assist in the comparison of relationships. The first layer captures fundamental, primitive relationships based upon well-known work in data abstractions and conceptual modeling. The second layer captures the life cycle of natural progressions in the business world. The third layer reflects the context-dependent nature of relationships. Use of the classification scheme is illustrated by comparing relationships from various application domains with different purposes.
This research was partially supported by J. Mack Robinson College of Business, Georgia State University and Pennsylvania State University.
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References
Bergholtz, M., Johnannesson, P.: Classifying the Semantics of Relationships in Conceptual Modelling by Categorization of Roles. In: Proceedings of the 6th International Workshop on Applications of Natural Language to Information Systems (NLDB 2001), Madrid, Spain, June 28-29 (2001)
Biskup, J., Embley, D.W.: Extracting Information from Heterogeneous Information Sources using Ontologically Specified Target Terms. Information Systems 28(3) (2003)
Brachman, R.J.: What IS-A is and Isn’t: An Analysis of Taxonomic Links in Semantic Networks. IEEE Computer (October 1983)
Brodie, M.: Association: A Database Abstraction. In: Proceedings of the Entity-Relationship Conference (1981)
Chen, P.: The Entity-Relationship Approach. In: Information Technology in Action: Trends and Perspectives, pp. 13–36. Prentice Hall, Englewood Cliffs (1993)
Coad, P., et al.: Object Models: Strategies, Patterns, & Applications. Prentice Hall, Englewood Cliffs (1995)
Cottam, H.: Ontologies to Assist Process Oriented Knowledge Acquisition (2000), http://www.spede.co.uk/papers/papers.htm
Dahlgren, K.: Naive Semantics for Natural Language Understanding. Kluwer Academic Publishers, Hingham (1988)
Dullea, J., Song, I.-Y.: A Taxonomy of Recursive Relationships and Their Structural Validity in ER Modeling. In: Akoka, J., Bouzeghoub, M., Comyn-Wattiau, I., Métais, E. (eds.) ER 1999. LNCS, vol. 1728, pp. 384–389. Springer, Heidelberg (1999)
Embley, D., Campbell, D.M., Jiang, Y.S., Ng, Y.K., Smith, R.D., Liddle, S.W., Quass, D.W.: A Conceptual-modeling Approach to Web Data Extraction. Data & Knowledge Engineering (1999)
Fellbaum, V.: Introduction. In: Wordnet: An Electronic Lexical Database, pp. 1–19. The MIT Press, Cambridge (1998)
Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design patterns: elements of reusable object-oriented software. Addison-Wesley Longman Publishing Co., Inc., Boston (1995)
Goldstein, R.C., Storey, V.C.: Data Abstractions: “Why and How. Data and Knowledge Engineering 29(3), 1–18 (1999)
Gruninger, M., Fox, M.S.: Methodology for the Design and Evaluation of Ontologies. In: Proceedings of the Workshop on Basic Ontological Issues in Knowledge Sharing, IJCAI 1995, Montreal (1995)
Hay, D.C., Barker, R.: Data Model Patterns: Conventions of Thought. Dorset House (1996)
Kedad, Z., Metais, E.: Dealing with Semantic Heterogeneity During Data Integration. In: Akoka, J., Bouzeghoub, M., Comyn-Wattiau, I., Métais, E. (eds.) ER 1999. LNCS, vol. 1728, pp. 325–339. Springer, Heidelberg (1999)
Larmon, C.: Applying UML and Patterns. Prentice-Hall, Englewood Cliffs (1997)
Miller, G.A., Beckwith, R., Fellbaum, C., Gross, D., Miller, K.J.: Introduction to WordNet: An On-line Lexical Database. International Journal of Lexicography 3(4), 235–244 (1990)
Motschnig-Pitrik, R., Myloppoulos, J.: Class and Instances. International Journal of Intelligent and Cooperative Systems 1(1), 61–92 (1992)
Motschnig-Pitrik, R.: A Generic Framework for the Modeling of Contexts and its Applications. Data and Knowledge Engineering 32, 145–180 (2000)
Noy, N.F., McGuinness, D.L.: Ontology Development 101: A Guide to Creating Your First Ontology (2001), Available at http://protege.stanford.edu/publications/ontology_development/ontology101-noy-mcguinness.html (accessed March 15 2004)
Smith, J., Smith, D.: Database Abstractions: Aggregation and Generalization. ACM Transactions on Database Systems 2(2), 105–133 (1977)
Wand, Y., Storey, V.C., Weber, R.: Analyzing the Meaning of a Relationship. ACM Transactions on Database Systems 24(4), 494–528 (1999)
Weber, R.: Ontological Issues in Accounting Information Systems. In: Sutton, S., Arnold, V. (eds.) Researching Accounting as an Information Systems Discipline (2002)
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Storey, V.C., Purao, S. (2004). Understanding Relationships: Classifying Verb Phrase Semantics. In: Atzeni, P., Chu, W., Lu, H., Zhou, S., Ling, TW. (eds) Conceptual Modeling – ER 2004. ER 2004. Lecture Notes in Computer Science, vol 3288. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30464-7_27
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DOI: https://doi.org/10.1007/978-3-540-30464-7_27
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