Novel and Efficient Hybrid Strategies for Constraining the Search Space in Frequent Itemset Mining
Association rule mining was originally applied in market basket analysis which aims at understanding the behaviour and shopping preferences of retail customers. The knowledge is used in product placement, marketing campaigns, and sales promotions. In addition to the retail sector, the market basket analysis framework is also being extended to the health and other service sectors. The application of association rule mining now extends far beyond market basket analysis and includes detection of network intrusions, attacks from Web server logs, and prediciting user traversal patterns on the Web.
KeywordsFrequent Itemsets Hybrid Strategy Frequent Itemset Mining Sample Database Dense Dataset
Unable to display preview. Download preview PDF.
- 1.Ceglar, A. and Roddick, J.F. (2006). Association mining, ACM Computing Surveys, vol. 38, no. 2.Google Scholar
- 2.Agrawal, R., Imielinski T., and Swami, A. (1993). Mining association rules between sets of items in large databases, ACM SIGMOD Conference on Management of Data.Google Scholar
- 4.Shenoy, P. et al. (2000). Turbo charging vertical mining of large databases, International Conference on Management of Data.Google Scholar
- 6.Zaki, M.J. and Gouda, K. (2003). Fast vertical mining using diffsets, SIGKDD’.Google Scholar