A Model for Vague Association Rule Mining in Temporal Databases
Year: 2013
Journal of Information and Computing Science, Vol. 8 (2013), Iss. 1 : pp. 63–74
Abstract
There are different university offering different types of courses over several years, and the biggest issue with that is how to get information to make course more effective. In real life these types of database usually contain temporal coherences, which cannot be captured by means of standard association rule mining. Here temporal Association rule mining can be used to evaluate the course effectiveness and helps to look for in regards to changes in performance of the course from time to time. For Example there is a course offering different topics. We can say that the topics having full attendance are totally effective and carry no hesitation information. While there are some topics which are almost fully attendant carry some hesitation information. This hesitation information is valuable and can be used to make the course more effective and interesting. Thus there is need for developing temporal vague association rule algorithms that reveal such hesitation information and temporal coherences within this data.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2024-JICS-22629
Journal of Information and Computing Science, Vol. 8 (2013), Iss. 1 : pp. 63–74
Published online: 2013-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 12