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Ayorinde I. T. , Akinkunmi B. O. and Alao Y. M.

International Conference on Transition from Observation to Knowledge to Intelligence (TOKI) – August 20-22, 2014. PAPER PRESENTATION ON Course Registration Ontology for Students (A Case Study of Computer Science Department, University of Ibadan).

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Ayorinde I. T. , Akinkunmi B. O. and Alao Y. M.

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  1. International Conference on Transition from Observation to Knowledge to Intelligence (TOKI) – August 20-22, 2014. PAPER PRESENTATION ONCourse Registration Ontology for Students (A Case Study of Computer Science Department, University of Ibadan) Ayorinde I. T. , Akinkunmi B. O. and Alao Y. M. Computer Science Department, University of Ibadan, Ibadan, Nigeria AUGUST, 2014.

  2. Presentation • Introduction • Aim & Objectives • Methods & Materials • Implementation • Conclusion • Future Direction • References

  3. Introduction • Ontology defines a set of representational primitives with which to model a domain of knowledge or discourse. The representational primitives are typically classes, attributes and relationships. (Gruber 2009). • The definitions of the representational primitives include information about their meaning and constraints on their logically consistent application.

  4. Introduction Contd. • Ontology can be viewed as a level of abstraction of data models, analogous to hierarchical and relational models, but intended for modeling knowledge about individuals, their attributes, and their relationships to other individuals. • Ontologies are typically specified in languages that allow abstraction away from data structures and implementation strategies; in practice, the languages of ontologies are closer in expressive power to first-order logic or descriptive logic than languages used to model databases (Gruber 1993).

  5. Introduction Contd. • Ontologies are said to be at the "semantic" level, whereas database schema are models of data at the "logical" or "physical" level. • Course registration is the act of registering students properly for different courses with respect to their levels.

  6. Aim & Objectives • The aim of this research work is to build an ontology on course registration for students. The objectives are: • To forestall the perpetual mistakes being made by the students during course registration at the beginning of every academic session. • To guide students on proper registration in order to have better CGPAs (Especially the weak ones).

  7. Methods and Materials The ontology’s requirements were defined using the following competency questions: • What is the minimum number of course units to register for in a session? • What courses are to be taken in each of the levels? • What is the procedure for registration? • What necessary information does a student need from his/her level adviser?

  8. Methods and Materials Contd. Conceptual Modeling of the Domain The following steps were taking in building the course registration ontology for students: • defining classes in the ontology, • arranging the classes in a taxonomic (subclass–superclass) hierarchy, • defining slots and describing allowed values for these slots, • filling in the values for slots for instances. • defining relationships among the various entities • We used Protégé 4.1 (an ontology editor) to model the class hierarchy.

  9. Methods and Materials Contd. Relationships Between Entities. • A STUDENT IS_IN a LEVEL • A STUDENT OFFERS some COURSES • Some COURSES are OFFERED in a LEVEL • Some COURSES have PREREQUISITES in Some LEVELS • Some COURSES are being OFFERRED BY a STUDENT (This is an inverse functional requirement to “A STUDENT OFFERS some COURSES” • COURSE_CODE HAS TITLE • COURSE_CODE HAS UNIT

  10. Implementation Fig. 1: Ontograph Showing the various steps needed for registration

  11. Implementation Contd. Fig. 2: Ontograpgh Showing the Basic Things to get from a Level Adviser

  12. Implementation Contd. Fig. 3: Result of a Query Showing 100 Level Courses

  13. Implementation Contd. Fig. 4: Ontograph of Relationship Between Student and Courses

  14. CONCLUSION • The relevant concepts which characterize the domain of discourse has been identified, appropriately defined along with their binding relationships and slots, and has been classified based on the inherent concepts they describe. • The concept has been presented using a tree-like class hierarchy which shows the relationship between the super-class concept and the sub-class concepts. • Hence, an error free, reliable and efficient registration process that will guide the students on how to register their courses has been presented here. • This ontology is actually a Transition from Observation to Knowledge to Intelligence.

  15. Future Directions • We intend to expand the scope of this ontology to all the departments in the University of Ibadan and also build more relationships among the entities.

  16. REFERENCES REFERENCES • Gruber T. R. (1993). Toward Principles for the Design of Ontologies Used for Knowledge Sharing. Knowledge Systems Laboratory (KSL), Stanford University, 1993). • Gruber T. R. (2009). “Ontology” (in the Encyclopedia of Database Systems, Ling Liu and M. Tamer Özsu (Eds.)), Springer-Verlag, 2009. • Farquhar A., Fikes R. and Rice J. (1997). “The Ontolingua Server: A Tool for Collaborative Ontology Construction.” International Journal of Human- Computer Studies, vol. 46, No. 6, June 1,1997, pp. 707-727.  • Bateman, J. A. (1995). On the Relationship Between Ontology Construction and Natural Language: a Socio-Semiotic View. International Journal of Human-Computer Studies. Vol 9, No 3, pg 15-21. • Fikes R. , Farqhuar A. and Rice J. (1997). Tools for Assembling Modular Ontologies in Ontolingua, Tech. Report KSL-97-03, Knowledge Systems Laboratory, April, 1997, Stanford University. • Swartout, W., & Tate, A. (1999). Ontologies, Guest Editors' Introduction. IEEE Intelligent Systems 14(1), pg 18-19. • Genesereth M. R. and Nilsson N. J. (1987). Logical Foundation of Artificial Intelligence. Morgan Kaufmann, Los Altos, California.

  17. THANK YOU

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