FHN: Efficient Mining of High-Utility Itemsets with Negative Unit Profits
نویسنده
چکیده
High utility itemset (HUI) mining is a popular data mining task. It consists of discovering sets of items generating high profit in a transaction database. Several efficient algorithms have been proposed for this task. But few can handle items with negative unit profits despite that such items occurs in many real-life transaction databases. Mining HUIs in a database where items have positive and negative unit profits is a very computationally expensive task. To address this issue, we present an efficient algorithm named FHN (Faster High-Utility itemset miner with Negative unit profits). FHN discovers HUIs without generating candidates and introduces several strategies to handle items with negative unit profits efficiently. Experimental results with six real-life datasets shows that FHN is up to 500 times faster and can use up to 250 times less memory than the state-of-the-art algorithm HUINIV-Mine.
منابع مشابه
A New Algorithm for High Average-utility Itemset Mining
High utility itemset mining (HUIM) is a new emerging field in data mining which has gained growing interest due to its various applications. The goal of this problem is to discover all itemsets whose utility exceeds minimum threshold. The basic HUIM problem does not consider length of itemsets in its utility measurement and utility values tend to become higher for itemsets containing more items...
متن کاملAn Efficient Three-Scan Approach for Mining High Utility Itemsets
Utility mining finds out high utility itemsets by considering both the profits and quantities of items in transactions. In this paper, a three-scan mining approach is proposed to efficiently discover high utility itemsets from transaction databases. The proposed approach utilizes an itemset-generation mechanism to prune redundant candidates early and to systematically check the itemsets from tr...
متن کاملMining high on-shelf utility itemsets with negative values from dynamic updated database
Utility mining emerged to overcome the limitations of frequent itemset mining by considering the utility of an item. Utility of an item is based on user’s interest or preference. Recently, temporal data mining has become a core technical data processing technique to deal with changing data. On-shelf utility mining considers on-shelf time period of item and gets the accurate utility values of it...
متن کاملInternational Journal of advanced studies in Computer Science and Engineering
Utility mining emerged to overcome the limitations of frequent itemset mining by considering the utility of an item. Utility of an item is based on user’s interest or preference. Recently, temporal data mining has become a core technical data processing technique to deal with changing data. On-shelf utility mining considers on-shelf time period of item and gets the accurate utility values of it...
متن کاملA Novel Algorithm for Mining Fuzzy High Utility Itemsets
Utility mining is to find the itemsets in a transaction database with high utility values like profits. Although a number of algorithms on high utility mining have been proposed, they did not reflect the fuzzy degree of quantity and profit level for mined high utility itemsets, which are essential for decision making in various applications like stock control and sales analysis. In this paper, ...
متن کامل