Abstract Deletion of transactions in databases is common in real-world applications. Developing an efficient and effective mining algorithm to maintain discovered information is thus quite important in data mining fields. A lot of algorithms have been proposed in recent years, and the best of them is the pre-large-tree-based algorithm. However, this algorithm only rebuilds the final pre-large tree every deleted transactions. After that, the FP-growth algorithm is applied for mining all frequent item sets. The pre-large-tree-based approach requires twice the computation time needed for a single procedure. In this paper, we present an incremental mining algorithm to solve above issues. An itemset tidset-tree structure will be used to maintain large and pre-large item sets. The proposed algorithm only processes deleted transactions for updating some nodes in this tree, and all frequent item sets are directly derived from the tree traversal process. Experimental results show that the proposed algorithm has good performance.

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[22] Zaki M., Scalable Algorithms for Association Mining, IEEE Transactions on Knowledge and Data Engineering, vol. 12, no. 3, pp. 372-390, 2000. Bay Vo received his PhD degrees in Computer Science from the University of Science, Vietnam National University of Ho Chi Minh, Vietnam in 2011. His research interests include association rules, classification, mining in incremental database, distributed databases and privacy preserving in data mining. Thien-Phuong Le received his MSc degrees in Information System from the University of Science, Vietnam National University of Ho Chi Minh, Vietnam in 2011. His research interests include association rules, clustering, classification, mining in incremental databases. Tzung-Pei Hong received his PhD degree in computer science and information engineering from National Chiao-Tung University in 1992. He served as the first director of the library and computer center, the Dean of Academic Affairs and the Vice President in National University of Kaohsiung. He is currently a distinguished professor at the Department of Computer Science and Information Engineering in NUK. He has published more than 400 research papers in international/national journals and conferences and has planned more than fifty information systems. He is also the board member of more than thirty journals and the program committee member of more than two hundreds conferences. His current research interests include parallel processing, machine learning, data mining, soft computing, management information systems and www applications. Bac Le received the BSc degree, in 1984, the MSc degree, in 1990, and the PhD degree in Computer Science, in 1999. He is an Associate Professor, Vice Dean of Faculty of Information Technology, Head of Department of Computer Science, University of Science, Ho Chi Minh City. His research interests are in artificial intelligent, soft computing, and knowledge discovery and data mining. 602 The International Arab Journal of Information Technology, Vol. 13, No. 5, September 2016 Jason Jung is an associate professor of Computer Engineering Department at Chung-Ang University, Korea. He was a postdoctoral researcher in INRIA Rhone-Alpes, France in 2006, and a visiting scientist in Fraunhofer Institute (FIRST) in Berlin, Germany in 2004. He received the B.Eng. in Computer Science and Mechanical Engineering from Inha University in 1999. He received M.S. and Ph.D. degrees in Computer and Information Engineering from Inha University in 2002 and 2005, respectively. His research topics are knowledge engineering on social networks by using machine learning, semantic Web mining, and ambient intelligence. He has about 25 international journal articles published in Knowledge-Based Systems, Information Retrieval, Information Processing & Management, Knowledge and Information Systems, and Expert Systems with Applications. Also, he is an editorial member of Journal of Universal Computer Science and International Journal of Intelligent Information and Database Systems. Moreover, he has been editing 10 special issues in Information Sciences, Journal of Network and Computer Applications, Computing and Informatics and so on.