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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Suh, S.C. Gaddam, L. |
| Copyright Year | 2011 |
| Description | Author affiliation: Department of Computer Science, Texas A&M University - Commerce, 75429, USA (Suh, S.C.; Gaddam, L.) |
| Abstract | Ontology is a technique that represents data as a set of concepts within a domain and the relativity of those concepts [16]. It is used to give the rationale to the entities within the domain, and can also be used to describe about it [21]. Clustering organizes data into individual clusters. In this article we are proposing a model which uses the hierarchical relationships. We group related item sets to form clusters utilizing relational ontology. Relational ontology varies from domain to domain. As the name suggests relational ontology is more about relations. It represents the relativity of attributes and concepts. By performing clustering on the relational ontology we derived new relations through which, we can generate the new rules learnt from the database. In this article we have chosen the preventive health care domain through nutrition as an instance to show how effective is relational ontology to represent the existing data and to generate the further knowledge in the database. |
| Starting Page | 126 |
| Ending Page | 132 |
| File Size | 1825173 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781457711282 |
| e-ISBN | 9788988678619 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-09-26 |
| Publisher Place | Korea (South) |
| Access Restriction | Subscribed |
| Rights Holder | AICIT |
| Subject Keyword | Proteins Concepts Databases Relational ontology Calcium Ontology relation Combined relations Ontologies Minerals Contributed attributes Clustering Diseases |
| Content Type | Text |
| Resource Type | Article |
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