Review of High Utility Pattern Mining Algorithms Focused On Memory Utilization  
  Authors : Shilpa Ghode


Discovering interesting patterns and useful knowledge from massive data has become an important data mining task. These days, we come across a lot of things that have profit technically referred as external utility, value greater than the other item sets in the database. Utility mining is an important topic in data mining and has received extensive research in last few years. In utility mining, each item is associated with a utility that could be profit, quantity, cost or other user preferences. Objective of Utility Mining is to identify the item sets with highest utilities. High utility itemset mining is an extension to the problem of frequent pattern mining. Many algorithms have been proposed in this field in the recent years. In this paper we emphasis on an emerging area called High Utility Mining which not only considers the frequency of the itemsets but also considers the utility associated with the itemsets. In High Utility Itemset Mining the target is to identify itemsets that have utility value greater than the threshold utility value. In this paper we present a review of the various techniques and current scenario of research in mining high utility itemset also presented advantages and limitations of various techniques for High Utility Itemset Mining. We mainly focus on the D2HUP and MAHUSP approach and algorithms for high utility pattern mining with less memory utilization.


Published In : IJCAT Journal Volume 5, Issue 3

Date of Publication : March 2018

Pages : 22-27

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Publication Link :Review of High Utility Pattern Mining Algorithms Focused On Memory Utilization




Shilpa Ghode : Asst. Prof. In Computer Technology Department Kavikulguru Institute of Technology and Science, Ramtek








Data mining, Frequent Patterns, High Utility Pattern Mining, High Utility Itemsets, High Utility Mining Algorithms

A Utility mining is an apparent topic in data mining. The main focus in the field of Utility Mining is not only Frequent Itemset Mining but also the consideration of utility. Practically it has been found that the utility is of great interest in industry if considers with high utility itemsets. This research paper presents a review of various existing high utility itemset mining algorithms. The reviewed algorithms effectively mining high utility itemsets based on the various data structure and constraint techniques. This will be helpful for developing new efficient and optimize techniques for high utility itemset mining. However to discover patterns for large transactional datasets an effective high utility pattern mining algorithm is required for improving the performance and search space of high utility itemsets. As the concept of High Utility Itemset Mining has a vast opportunities to be researched, the future work will incorporate soft computing methodologies for high utility itmesets mining such as the intuitionistic fuzzy logic can be explored in the field of High Utility Itemset Mining and its memory consumption.










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