A. Sheth, J. Larson, A. Cornelio, and S. B. Navathe. A tool for integrating conceptual schemata and user views. In Proceedings of the 4th International Conference on Data Engineering, pages 176-183. IEEE, February 1988.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....comparison can lead to unintended correspondences or fail to detect important ones. Other promising methodologies that were developed include heuristics to determine the similarity of objects based on the percentage of occurrences of common attributes [ Hayne and Ram, 1990; Navathe et al. 1986; Sheth et al. 1988 ] More accurate techniques use classi cation for choosing a possible relationship between classes [ Savasere et al. 1991 ] Whereas most of these methods primarily utilize schema knowledge, techniques utilizing semantic knowledge (based on real world experience) have also been investigated. ....

A. Sheth, J. Larson, A. Cornelio, and S. B. Navathe. A tool for integrating conceptual schemata and user views. In Proceedings of the 4th International Conference on Data Engineering, pages 176-183. IEEE, February 1988.

....reasoning, the alternatives can be ordered according to their likelihood. Applying uncertainty reasoning to the evaluation of rules forms also a nice way to exploit the integration rules directly in order to determine the similarity of schema entries, rather than using separate heuristics as in, Sheth et al. 88] Fang et al. 91] Similar techniques can also be utilized to deal with local schema evolution. For example, if originally books were represented as Book: title: string] and accordingly a (partial) one to one correspondence between Monography and Book via Monography.heading = Book.title was ....

A. Sheth, J. Larson, A. Cornelio, S.B. Navathe: "A Tool for Integrating Conceptual Schemata and User Views"; Proceedings of the 4th International Conference on Data Engineering; Feb. 1988; pp. 176--183

....to test such normal forms for equivalences, subsumption, overlap, and inconsistencies; and to generate, on this basis, integrated schema constituents and their mappings to the underlying schemas. Several rule based tools for schema integration have already been prototyped, for example, SLCN88] HR90] These tools support mainly the retrieval of similar schema constituents and the generation of integrated schemas based on declarative correspondence assertions given by the user. However, these tools typically aim at a single completely integrated schema, do not offer adequate support ....

A. Sheth, J. Larson, A. Cornelio, and S. Navathe. A Tool for Integrating Conceptual Schemata and User Views. In Proceedings IEEE Data Engineering Conference, 1988, pp. 176--183.

....meaning of an object, and thus their comparison can lead to unintended correspondences or fail to detect important ones. Other promising methodologies that have been developed include heuristics to determine the similarity of objects based on the percentage of occurrences of common attributes [10, 23]. More accurate techniques use classification for choosing a possible relationship between classes [21] Whereas most of previous methods primarily utilize schema knowledge, techniques utilizing semantic knowledge (based on real world experience) have also been investigated [5, 12] These ....

A. Sheth, J. Larson, A. Cornelio, and S. B. Navathe. A Tool for Integrating Conceptual Schemata and User Views. In Proceedings of the 4th International Conference on Data Engineering, pages 176--183. IEEE, February 1988.

....comparison of schemas, conforming of schemas, merging, restructuring) However, most of the approaches examined in this survey do not directly address the diversity problem described above. The problem of achieving semantic interoperability has been studied extensively in view integration [3, 18, 39, 41, 48] using the relational and semantic data models, but (partial) unification of multiple heterogeneous object based databases is still in its infancy. Research in the area of heterogeneous database systems (HDBSs) began only a decade ago [13, 51] The term heterogeneous databases was originally ....

....meaning of an object, and thus their comparison can lead to unintended correspondences or fail to detect important ones. Other promising methodologies that were developed include heuristics to determine the similarity of objects based on the percentage of occurrences of common attributes [18, 41, 48]. More accurate techniques use classification for choosing a possible relationship between classes [45] Whereas most of these methods primarily utilize schema knowledge, techniques utilizing semantic knowledge (based on real world experience) have also been investigated. Fankhauser et al. 12] ....

A. Sheth, J. Larson, A. Cornelio, and S. B. Navathe. A Tool for Integrating Conceptual Schemata and User Views. In Proceedings of the 4th International Conference on Data Engineering, pages 176--183. IEEE, February 1988.

....out in the introduction, purely structural considerations do not suffice to determine the semantic similarity of classes. Consider for example the three schemas in Figure 2 2 . If we compute the percentage of common attributes proposed as heuristic for instance in [NEL86] and realized in [SLCN88] we get: CarOwner ResearchInstitute (66 ) CarOwner Person (57 ) ResearchInstitute Person (57 ) and 0 for the rest. However, intuitively CarOwner andPerson are semantically close, 2 We deliberately employ a very primitive syntax for class definition with only one simple domain string ....

A. Sheth, J. Larson, A. Cornelio, and S.B. Navathe. A tool for integrating conceptual schemata and user views. In Proc. of the 4th Int. Conf. on Data Engineering, pages 176--183, Feb. 1988.

....meaning of an object, and thus their comparison can lead to unintended correspondences or fail to detect important ones. Other promising methodologies that have been developed include heuristics to determine the similarity of objects based on the percentage of occurrences of common attributes [10, 22]. More precise techniques use classification for choosing a possible relationship between classes [21] In addition to methods primarily utilizing schema knowledge, techniques based upon the use of semantic knowledge (based on real world experience) have also been investigated [6, 12] These ....

A. Sheth, J. Larson, A. Cornelio, and S. B. Navathe. A Tool for Integrating Conceptual Schemata and User Views. In Proceedings of the 4th International Conference on Data Engineering, pages 176--183. IEEE, February 1988.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC