Utility mining is a key rising field in data mining, meant to reveal High Utility Item sets (HUIs), from a dataset.

engineering

Description

An efficient technique for High Utility Item sets Retrieval in Multi-level database

 

 


Abstract

Utility mining is a key rising field in data mining, meant to reveal High Utility Item sets (HUIs), from a dataset. The item sets with utility value greater than a previously mentioned threshold arereferred to as HUIs. Several algorithms were projected to date, to retrieve HUIs in a single level database. As per the literature survey, no utility mining algorithms is proposed for multiple level dataset. The main objective of this work is to retrieve HUIs from a multi-level dataset. In this work, a unique multi-level utility mining algorithm namely MUMA (Multilevel Utility Mining Algorithm) was proposed to retrieve HUIs in a multi-level dataset. The MUMA algorithm implements a tree structure known as MUMT (Multilevel Utility Mining Tree), to store utility information of the item sets. Candidate item sets are generated from this tree thereby reduces the space complexity of the algorithm. The research work also proposed an enhanced tree-based algorithm namely Multi-level Utility Mining using Enumeration Tree (MU_ET), Multi-level Utility Mining using Utility pattern Tree (MU_UP), Multi-level Utility Mining using Lexicographic Tree (MU_LG). Since there are no existing multi-level utility algorithms in the literature, MUMA was compared with MU_ET, MU_UP and MU_LG and performance are analyzed. The experiments are done using different datasets like transaction datasets, weblogdatasets,and synthetic datasets. Performance factors like execution time, Memory space, number of potential high utility items and number of HUIs retrieved in each level was evaluated in each dataset.

Keywords: Utility mining, Multi-level utility mining, Multi-level High utility item sets, Multiple utility threshold, Multilevel Utility Mining Tree.


1. INTRODUCTION

B

usiness Analytics is the analyses of historical organization information, for the data-focused higher cognitive decision-making process in business. The organizations use business analytics to systemize and enhance the business processes. Recognizing profitable items is a crucial task in business analytics. Understanding the foremost profit-making customers and the profitable product is essential in themostdecision-making scenario like making a lot of profitable offers, equalization the profitable product sales and characteristic the simplest targets for brand spanking new product. Utility mining is a recent rising field of data mining, accustomed fetch high cash creating item sets in an exceedingly retail business information.[1] [2] .

 

[1]

 

1.1. Utility Minining

Utility refers to a linguistics measure and can be applied to a transaction database [3] [4] [5]. Utility mining was introduced to beat the deficiency of frequent itemset mining. The deficiency of frequent itemset mining was that it counts the number of the existence of the items in a database, not the profit of the items[6]. Hence utility mining was introduced to contemplate these factors. The intention of utility mining is to fetch high utility item sets from a database [7] [8] [9].This is done by shrewd utility values of all item sets in a database and to retrieve the item sets whose utility value is larger than utility threshold.

The utility will be applied to item/item set in a transaction, item/item set in a database or to a transaction itself [2] [10] [11].These calculations will be done based on the following definitions.[9] [10] [12] [13] [14] [15]

 

Definition 1:The external utility of item I1, symbolized as exu(I1), is the unit profit of the item I1 mentioned in the utility table.

Definition 2:The internal utility of item I1 in transaction T1, symbolized as inu(I1, T1), is the quantity of item sold in a transaction T1.

Definition 3:The utility of itemI1 in transaction T1, symbolized as u(I1, T1), is the product of inu(I1, T1) and exu(I1), where u(I1, T1) = inu(I1, T) × exu(I1).

Definition 4:The utility of itemset S in transaction T1, symbolized as u(S,T1), is the sum of the utilities of all the items in S in T1, i.eu(S,T1)=ΣiSST u(I, T1).

Definition 5:The utility of itemset S, symbolized as u(S), is the sum of the utilities of S in all the transactions containing S in the database(DB), i.e u (S)=ΣTDB ST u(S,T).

Definition 6: The transaction utility (TU) of a transaction T1, symbolized as TU(T1), is the sum of the utilities of items in T1, i.e  TU(T1) =ΣIT TDB u(I,T).

Definition 7: The Transaction weighted utility of itemI1symbolized as TWU(I1) is the sum of all transaction utility (TU) in which the item I1 appears.

Definition 8: An itemset S in a database DB points out as a high-utility itemset (HUI) if its utility value exceeds minimum utility threshold.



 


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