dc.contributor.author |
Gohel, Milan N. |
|
dc.date.accessioned |
2024-11-20T07:29:05Z |
|
dc.date.available |
2024-11-20T07:29:05Z |
|
dc.date.issued |
2023-05 |
|
dc.identifier.citation |
Gohel, M. N. (2023). An Examination of High Utility Item Set Mining using Different Techniques. International Journal of Innovative Science and Research Technology, 8(5), 2456-2165. |
en_US |
dc.identifier.issn |
2456-2165 |
|
dc.identifier.uri |
http://10.9.150.37:8080/dspace//handle/atmiyauni/1761 |
|
dc.description.abstract |
Finding high utility itemset from transaction databases refers to finding itemset that are profitable and useful. Frequent Itemset mining, which identifies often occurring itemsets, is expanded upon in Itemset Utility Mining. Recognising itemsets with utility values over a certain ven utility threshold is the aim of high utility itemset mining. The user-specified minimum support threshold value must be met for an itemset to be considered a high utility itemset; otherwise, it is treated as a low utility itemset. In this article, we give a literature review of the current state of research, as well as a look at different algorithms and their potential drawbacks for high utility dataset mining. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
International Journal of Innovative Science and Research Technology |
en_US |
dc.relation.ispartofseries |
8;5 |
|
dc.subject |
Mining of association rules |
en_US |
dc.subject |
Frequent itemsets |
en_US |
dc.subject |
High utility itemsets |
en_US |
dc.title |
An Examination of High Utility Item Set Mining using Different Techniques |
en_US |
dc.type |
Article |
en_US |