Succinct summarization of transactional databases: an overlapped hyperrectangle scheme

Transactional data are ubiquitous. Several methods, including frequent itemsets mining and co-clustering, have been proposed to analyze transactional databases. In this work, we propose a new research problem to succinctly summarize transactional databases. Solving this problem requires linking the high level structure of the database to a potentially huge number of frequent itemsets. We formulate this problem as a set covering problem using overlapped hyperrectangles; we then prove that this problem and its several variations are NP-hard. We develop an approximation algorithm HY PER which can achieve a ln(k) + 1 approximation ratio in polynomial time. We propose a pruning strategy that can significantly speed up the processing of our algorithm. Additionally, we propose an efficient algorithm to further summarize the set of hyperrectangles by allowing false positive conditions. A detailed study using both real and synthetic datasets shows the effectiveness and efficiency of our approa...

• Type: Conference
• Year: 2008
• Where: KDD
• Authors: Yang Xiang, Ruoming Jin, David Fuhry, Feodor F. Dragan
• Keywords: Approximation Algorithm Hy, Data Mining, KDD 2008, Set Covering Problem, Transactional Databases