A Review of some Popular High Utility Itemset Mining Techniques |
Author(s): |
Abhishek Raghuwansi , MIT, Ujjain (M.P.), India; Pradeep K. sharma, MIT, Ujjain (M.P.), India |
Keywords: |
Frequent itemset mining, Utility mining, High Utility Itemset, candidate pruning. |
Abstract |
Data Mining can be defined as an activity that extracts some new nontrivial information contained in large databases. Traditional data mining techniques have focused largely on detecting the statistical correlations between the items that are more frequent in the transaction databases. Like frequent item set mining, these techniques are based on the rationale that item sets which appear more frequently must be of more importance to the user from the business perspective. In this thesis we throw light upon an emerging area called Utility Mining which not only considers the frequency of the item sets but also considers the utility associated with the item sets. The term utility refers to the importance or the usefulness of the appearance of the item set in transactions quantified in terms like profit, sales or any other user preferences. In High Utility Item set Mining the objective is to identify item sets that have utility values above a given utility threshold. In this thesis we present a literature review of the present state of research and the various algorithms for high utility item set mining. |
Other Details |
Paper ID: IJSRDV1I9046 Published in: Volume : 1, Issue : 9 Publication Date: 01/12/2013 Page(s): 1875-1877 |
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