主催: The Japanese Society for Artificial Intelligence
会議名: 2013年度人工知能学会全国大会(第27回)
回次: 27
開催地: 富山県富山市 富山国際会議場
開催日: 2013/06/04 - 2013/06/07
In the past, utility mining was proposed to measure the utility values of purchased items for revealing high utility itemsets from a quantitative database. In dynamic data mining, transactions may be inserted, or deleted in the database. A batch mining procedure must rescan the whole updated database to maintain the up-to-date information. In this paper, a decremental mining algorithm is thus proposed for efficiently maintaining the discovered high utility itemsets due to transaction deletion based on the pre-large concept. Experimental results show that the proposed decremental high utility mining algorithm outperforms existing batch algorithms.