A Model for Vague Association Rule Mining in Temporal Databases
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@Article{JICS-8-063,
author = {Anjana Pandey and K.R.Pardasani},
title = {A Model for Vague Association Rule Mining in Temporal Databases},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {8},
number = {1},
pages = {063--074},
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.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22629.html}
}
TY - JOUR
T1 - A Model for Vague Association Rule Mining in Temporal Databases
AU - Anjana Pandey and K.R.Pardasani
JO - Journal of Information and Computing Science
VL - 1
SP - 063
EP - 074
PY - 2024
DA - 2024/01
SN - 8
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22629.html
KW - Hesitation Information, Vague Association Rule, AH pair,Temporal database.
AB - 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.
Anjana Pandey and K.R.Pardasani. (2024). A Model for Vague Association Rule Mining in Temporal Databases.
Journal of Information and Computing Science. 8 (1).
063-074.
doi:
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