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A Study on WT-Algorithm for Effective Reduction of Association Rules
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 Title & Authors
A Study on WT-Algorithm for Effective Reduction of Association Rules
Park, Jin-Hee; Pi, Su-Young;
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 Abstract
We are in overload status of information not just in a flood of information due to the data pouring from various kinds of mobile devices, online and Social Network Service(SNS) every day. While there are many existing information already created, lots of new information has been created from moment to moment. Linkage analysis has the shortcoming in that it is difficult to find the information we want since the number of rules increases geometrically as the number of item increases with the method of finding out frequent item set where the frequency of item is bigger than minimum support in this information. In this regard, this thesis proposes WT-algorithm that represents the transaction data set as Boolean variable item and grants weight to each item by making algorithm with Quine-McKluskey used to simplify the logical function. The proposed algorithm can improve efficiency of data mining by reducing the unnecessary rules due to the advantage of simplification regardless of number of items.
 Keywords
Big data;Association Rules;Weight;Data mining;
 Language
Korean
 Cited by
1.
연관성 방향을 고려한 부호 헬링거 측도의 제안,박희창;

Journal of the Korean Data and Information Science Society, 2016. vol.27. 2, pp.353-362 crossref(new window)
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