A comparative study of fuzzy logic and weighted Association rule mining in frequent datasets
Journal Title: International Journal of Computer Science & Engineering Technology - Year 2014, Vol 5, Issue 9
Abstract
Mining of frequent patterns in transaction databases has been a fashionable area of research. Many methods are being used to solve the trouble of discovering association rules among items in large databases [8]. Transaction pattern base have been introduced to reduce the number of passes over the database. Here considers the problem of using support for generating association rule. The classical associations rule mining frameworks assume that all items have the same significance that their weight within a transaction is the same which is not always the case. Here proposed the use of weighted support along with the transaction pattern which increases the efficiency in generating association rule using matrix manipulation[5] [3].
Authors and Affiliations
K. Rubia , S. Sasikala
Keywords
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