International Journal of Emerging Trends & Technology in Computer Science
A Motivation for Recent Innovation & Research
ISSN 2278-6856
www.ijettcs.org

Call for Paper, Published Articles, Indexing Infromation Survey on High Utility Itemset Mining from Large Transaction Databases, Authors : Ms.Yogita Khot, Mrs. Manasi Kulkarni, International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), www.ijettcs.org
Volume & Issue no: Volume 3, Issue 4, July - August 2014

Title:
Survey on High Utility Itemset Mining from Large Transaction Databases
Author Name:
Ms.Yogita Khot, Mrs. Manasi Kulkarni
Abstract:
Abstract Data mining can be defined as an activity that extracts some knowledge contained in large transaction databases. Conventional data mining techniques have focused largely on finding the items that are more frequent in the transaction databases, which is also called frequent itemset mining. These data mining techniques were based on supportconfidence model. Itemsets which appear more frequently in the database must be of more meaning to the user from the business point of view. In this paper we present an emerging area called as High Utility Itemset Mining that discovers the itemsets considering not only the frequency of the itemset but also utility associated with the itemset. Every itemset have a value like quantity, profit and other user’s interest. This value associated with every item in a database is called the utility of that itemset. Those itemsets having utility values greater than given threshold are called high utility itemsets. This problem can be identified as mining high utility itemsets from transaction database. In many areas of business like retail, inventory etc. decision making is very important. So it can help in mining algorithm, the presence of each item in a transaction database is represented by a binary value, without considering its quantity or an associated weight such as price or profit. However quantity, profit and weight of an itemset are significant for identifying real world decision problems that require increasing the utility in an organization. Mining high utility itemsets from transaction database presents a greater challenge as compared with frequent itemset mining, since anti-monotone property of frequent itemsets is not applicable in high utility itemsets. In this paper, we present a survey on the current state of research and the various algorithms and techniques for high utility itemset mining. Keywords: Data Mining, Frequent Itemset Mining, Utility Mining, High Utility Itemset Mining
Cite this article:
Ms.Yogita Khot, Mrs. Manasi Kulkarni , " Survey on High Utility Itemset Mining from Large Transaction Databases " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 3, Issue 4, July - August 2014 , pp. 299-301 , ISSN 2278-6856.
Full Text [PDF]                          Home