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Abstract

High-utility itemsets mining (HUIM) is a critical issue which concerns not only the occurrence frequencies of itemsets in association-rule mining (ARM), but also the factors of quantity and profit in real-life applications. Many algorithms have been developed to efficiently mine high-utility itemsets (HUIs) from a static database. Discovered HUIs may become invalid or new HUIs may arise when transactions are inserted, deleted or modified. Existing approaches are required to re-process the updated database and re-mine HUIs each time, as previously discovered HUIs are not maintained. Previously, a pre-large concept was proposed to efficiently maintain and update the discovered information in ARM, which cannot be directly applied into HUIM. In this paper, a maintenance (PRE-HUI-MOD) algorithm with transaction modification based on a new pre-large strategy is presented to efficiently maintain and update the discovered HUIs. When the transactions are consequentially modified from the original database, the discovered information is divided into three parts with nine cases. A specific procedure is then performed to maintain and update the discovered information for each case. Based on the designed PRE-HUI-MOD algorithm, it is unnecessary to rescan original database until the accumulative total utility of the modified transactions achieves the designed safety bound, which can greatly reduce the computations of multiple database scans when compared to the batch-mode approaches.

7. Conclusion and future work

In a real-life environment, a database is usually found in a dynamic environment as the transactions in the database are frequently inserted, deleted or modified. Transaction modification is also commonly seen in real-world applications, especially as errors or typos may frequently occur when information is inputted into a computer using a keyboard. Although transaction insertion is followed by transaction deletion, or deletion followed by insertion, can be concerned as a batch process for transaction modification, it takes twice operations and time-consuming processes to maintain and update the discovered HUIs. Thus, it is an important task to design a maintenance algorithm for transaction modification, and thus efficiently update the discovered HUIs in dynamic databases. In this paper, based on a new developed pre-large strategy, an efficient algorithm called PRE-HUI-MOD algorithm is proposed to maintain and update the discovered HUIs of HUIM for handling transaction modification. When transactions are modified, the proposed PRE-HUI-MOD algorithm partitions the discovered HTWUIs into three parts, creating nine cases according to whether they are HTWUIs or small transaction-weighted utilization itemsets in the original database and in the modified transactions. Each part is then executed by the designed procedure to respectively maintain and update the discovered HTWUIs. A safety bound is also designed to reduce database rescan computations when transactions are modified. From the experimental results, it can be observed that the proposed PRE-HUI-MOD algorithm outperforms existing batch-mode algorithms in several databases in terms of execution time and scalability