An Efficient Algorithm for Mining Closed High Utility Itemset
نویسنده
چکیده
Mining of High utility itemsets refers to discovering sets of data items that have high utilities. In recent years the high utility itemsets mining has extensive attentions due to the wide applications in various domains like biomedicine and commerce. Extraction of high utility itemsets from database is very problematic task. The formulated high utility itemset degrades the efficiency of the mining process. The existing algorithms suffer the problem of producing a large amount of candidates, which degrades the mining performance in terms of time and space. The Closed high utility itemset proposed to achieve this goal. In this paper, a novel algorithm has been proposed to discover the high utility itemset without candidates generation. Experimental results show that the proposed algorithm is faster than the state-ofthe-art algorithms Keywords—High utility itemset, closed high utility itemset, candidates generations. V.G.Vijilesh et al, International Journal of Computer Science and Mobile Computing, Vol.7 Issue.2, February2018, pg. 23-32 © 2018, IJCSMC All Rights Reserved 24
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 کاملEfficient Algorithms for Mining of High Utility Itemsets
--The utility of an itemset represents its importance, which can be measured in terms of weight, value, quantity or other information depending on the user specification. High utility itemsets mining identifies itemsets whose utility satisfies a given threshold. It allows users to quantify the usefulness or preferences of items using different values. Thus, it reflects the impact of different i...
متن کاملClohui: an Efficient Algorithm for Mining Closed
High-utility itemset mining (HUIM) is an important research topic in data mining field and extensive algorithms have been proposed. However, existing methods for HUIM present too many high-utility itemsets (HUIs), which reduces not only efficiency but also effectiveness of mining since users have to sift through a large number of HUIs to find useful ones. Recently a new representation, closed +...
متن کاملA Fast Algorithm for Mining Utility-Frequent Itemsets
Utility-based data mining is a new research area interested in all types of utility factors in data mining processes and targeted at incorporating utility considerations in both predictive and descriptive data mining tasks. High utility itemset mining is a research area of utilitybased descriptive data mining, aimed at finding itemsets that contribute most to the total utility. A specialized fo...
متن کاملAn efficient algorithm to mine high average-utility itemsets
With the ever increasing number of applications of data mining, high-utility itemset mining (HUIM) has become a critical issue in recent decades. In traditional HUIM, the utility of an itemset is defined as the sum of the utilities of its items, in transactions where it appears. An important problem with this definition is that it does not take itemset length into account. Because the utility o...
متن کامل