Abstract
Temporal High Utility Item (THUI) mining has become an emerging research topic in the data mining field, and finding frequent item sets is an important task in data mining with wide applications. Two basic factors to be considered in utility mining. First, the utility (e.g., profitability, time) of each item may be different in real applications; second, the frequent itemsets might not produce the highest utility. In this paper, we propose a novel algorithm named TOUIG (Temporal Optimal Utility Item Set Generation) which can find optimal high utility item sets from database. A novel approach namely, TOUI-tree (Temporal Optimal Utility Item set tree), is also proposed for efficiently capturing the utility of each item set with one-time scanning. The main contributions of this paper are as follows: 1) OUIG is the first one-pass utility-based algorithm for mining temporal optimal utility item sets and the experimental results show that our approach produces optimized solution than other existing utility mining algorithms.
