Survey on Incremental Association Rule Mining to find Frequent Itemsets |
Author(s): |
| suchi parekh , svit vasad; Neha R. soni, svit vasad |
Keywords: |
| Association rule, dynamic, incremental mining, frequent pattern mining |
Abstract |
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Mining frequent Itemsets has proved to be very difficult because of its computational complexity. But, , it has gained a lot of popularity due to the usefulness of association rules, despite having huge processing cost. This paper provides a comprehensive survey on the state-of-art algorithms for association rule mining, specially when the datasets used for rule mining are dynamic. When new data are added to a original dataset it may lead to additional rules or to modification of some existing rules. To find the association rules from the whole (old as well as new) dataset will be wastage of time only if the process is restarted from the beginning. Several algorithms have been developed to attend this important issue of the association rule mining problem. This paper analyzes some of the algorithms to tackle the incremental association rule mining problem. |
Other Details |
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Paper ID: IJSRDV2I11160 Published in: Volume : 2, Issue : 11 Publication Date: 01/02/2015 Page(s): 385-388 |
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