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A Foundational Approach to Mining Itemset Utilities from Databases [chapter]

Hong Yao, Howard J. Hamilton, Cory J. Butz
2004 Proceedings of the 2004 SIAM International Conference on Data Mining  
Most approaches to mining association rules implicitly consider the utilities of the itemsets to be equal.  ...  Our theoretical analysis of the resulting problem lays the foundation for future utility mining algorithms.  ...  Theorem 3.5 is the mathematical model of utility mining that we will use to design an algorithm to estimate the expected utility of a k−itemset from the known utilities of its high utility itemsets of  ... 
doi:10.1137/1.9781611972740.51 dblp:conf/sdm/YaoHB04 fatcat:czgricondzcj3khrsfl7n63dmu

A Conceptual Approach to Temporal Rare Item set Utility Mining

Jyothi Pillai, Sunita Soni, O.P. Vyas, Dr. Maybin Muyeba
2010 International Journal of Computer Applications  
In this paper, we present a theoretical conceptual approach to Temporal Weighted Itemset Utility Mining.  ...  Most Association Rule Mining (ARM) algorithms concentrate on mining frequent itemsets from crisp data and recently, use of discrete utility values.  ...  Conclusions and Future Work Our work presents a new foundational approach to temporal weighted itemset utility mining where item utility values are allowed to be dynamic within a specified period of time  ... 
doi:10.5120/510-827 fatcat:apc4qs24zzhl5dvonchqfcgizy

Overview of Itemset Utility Mining and its Applications

Jyothi Pillai, O.P. Vyas
2010 International Journal of Computer Applications  
Mining High Utility itemsets from a transaction database is to find itemsets that have utility above a user-specified threshold.  ...  Several researches about itemset utility mining were proposed. In this paper, a literature survey of various algorithms for high utility rare itemset mining has been presented.  ...  The authors in [22] presents a new foundational approach to temporal weighted itemset utility mining where item utility values are allowed to be dynamic within a specified period of time, unlike traditional  ... 
doi:10.5120/956-1333 fatcat:dro3py2glzaftkmxpfpn5rvv4e

Survey On Utility Data Mining

M Ganesan, S Shankar
2017 Zenodo  
The drawbacks of frequent itemset mining leads to consider a utility mining, which allows a user to conveniently express the usefulness of itemsets as utility values and then find itemsets with high utility  ...  In this paper, a literature survey of various high utility itemset mining algorithms has been presented.  ...  This utility bound property can be used as a heuristic measure for pruning itemsets at early stages that are not expected to qualify as high utility itemsets.  ... 
doi:10.5281/zenodo.813941 fatcat:boaxxi6k2vf2pei4epaplyuclm

Mining Low, Medium and High Profit Customers Over Transactional Data Stream

Vijay KumarVerma, Kanak Saxena
2014 International Journal of Computer Applications  
In Frequent Itemset Mining each item in transaction is represented by a binary value means 1 for present and 0 for absent.  ...  Quantity, price or and profit these parameter are important in retail markets to find high utility itemset.  ...  Butz Department of Computer Science proposed "A Foundational Approach to Mining Itemset Utilities from Databases".  ... 
doi:10.5120/16027-4867 fatcat:xrfxig6blrguhnpf33onscfvea

Implementation of Bio-Inspired Algorithms in High Utility Itemset Mining

2019 International Journal of Engineering and Advanced Technology  
on the application of bio-inspired algorithms on high utility itemset mining.  ...  Utility based itemset mining hasevolved as an important research topic in data mining, having application in retail-market data analysis, stock market prediction, online advertising and so on.  ...  To prune itemsets we can use a heuristic measure obtained from the utility bound property.  ... 
doi:10.35940/ijeat.f9078.109119 fatcat:kjd4iekdybdpzc3diwq5qojvmm

A Distributed Approach To Extract High Utility Itemsets From Xml Data

S. Kannimuthu, K. Premalatha
2014 Zenodo  
HUI mining is the one kind of utility mining concept, aims to identify itemsets whose utility satisfies a given threshold.  ...  In this work, a novel approach is proposed to mine HUIs from the XML based data in a distributed environment.  ...  [31] proposed a novel algorithm called Fast Utility Mining (FUM) to mine high utility itemsets from the databases.  ... 
doi:10.5281/zenodo.1091769 fatcat:qzrsiubaynh3fivaows4av2osa

Mining High Utility Itemsets from Large Dynamic Dataset by Eliminating Unusual Items

Switi C.Chaudhari, Vijay Kumar Verma
2013 International Journal of Computer Applications  
Mining high utility itemsets from the databases is not an easy task.  ...  Pruning search space for high utility itemset mining is difficult because a superset of a low utility itemset may be a high utility itemset.  ...  The limitations of frequent itemset mining motivated researchers to conceive a utility based mining approach.  ... 
doi:10.5120/13550-1315 fatcat:4tnpeio5fveslozl4m7ota6tyy

A Systematic Literature Review of Utility Itemset Mining Algorithms for Large Datasets

Vandna Dahiya
2021 Revista GEINTEC  
The mining of utility itemsets from a large dataset is a challenging issue because of the diverse dimensions of data.  ...  Various itemset mining algorithms have been projected by the researchers to discover relations among the items of a database.  ...  The aim is to find all such itemsets from the database. Foundations and Boundaries Various researchers have proposed several types of pattern mining techniques in the literature.  ... 
doi:10.47059/revistageintec.v11i3.1959 fatcat:hpbmpkn7mfhjpk6yulsv4cqcoy

Actionable high-coherent-utility fuzzy itemset mining

Chun-Hao Chen, Ai-Fang Li, Yeong-Chyi Lee
2014 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
Many fuzzy data mining approaches have been proposed for finding fuzzy association rules with the predefined minimum support from quantitative transaction databases.  ...  This is a modified and expanded version of the paper "A high coherent utility fuzzy itemsets mining algorithmon the foodmart and simulated datasets are made to show that the derived itemsets by the proposed  ...  Vo et al. (2009) proposed a method for mining high-utility itemsets from vertical distributed databases that uses a WIT-tree technique to scan the local database only once.  ... 
doi:10.1007/s00500-013-1214-4 fatcat:gsdygmg25rb6tjjcsldj3aq5oe

BAHUI

Wei Song, Yu Liu, Jinhong Li
2014 International Journal of Data Warehousing and Mining  
On the one hand, BAHUI exploits a divide-and-conquer approach to visit itemset lattice by using bitmap vertically.  ...  Although a number of relevant approaches have been proposed in recent years, they incur the problem of producing a large number of candidate itemsets for high utility itemsets.  ...  Otherwise, it is called a low utility itemset. Given a transaction database D, the task of high utility itemset mining is to find all itemsets that have utilities no less than min_util.  ... 
doi:10.4018/ijdwm.2014010101 fatcat:gwmwu2fs3zebjgobfhzcp3zsla

An Evolutionary Algorithm to Mine High-Utility Itemsets

Jerry Chun-Wei Lin, Lu Yang, Philippe Fournier-Viger, Jaroslav Frnda, Lukas Sevcik, Miroslav Voznak
2015 Advances in Electrical and Electronic Engineering  
High-utility itemset mining (HUIM) is a critical issue in recent years since it can be used to reveal the profitable products by considering both the quantity and profit factors instead of frequent itemset  ...  In this paper, an evolutionary algorithm is presented to efficiently mine high-utility itemsets (HUIs) based on the binary particle swarm optimization.  ...  To solve the limitation of FIM or ARM, high-utility itemset mining (HUIM) [20] , [21] , [22] was designed to discover the "useful" and "profitable" itemsets from the quantitative databases.  ... 
doi:10.15598/aeee.v13i4.1474 fatcat:mcxogast7nfpho4zeky36ycam4

Incrementally updating the high average-utility patterns with pre-large concept

Jerry Chun-Wei Lin, Matin Pirouz, Youcef Djenouri, Chien-Fu Cheng, Usman Ahmed
2020 Applied intelligence (Boston)  
High-utility itemset mining (HUIM) is considered as an emerging approach to detect the high-utility patterns from databases.  ...  High average-utility itemset mining (HAUIM) considers the size of the itemset, thus providing a more balanced scale to measure the average-utility for decision-making.  ...  Many extensions were also discussed to efficiently mine the set of HAUIs [32, 40, 41] . The aforementioned approaches consider the problem of mining from a static database.  ... 
doi:10.1007/s10489-020-01743-y fatcat:vxl77meb2nehroilekdrifhguu

Advance Mining of Temporal High Utility Itemset

Swati Soni, Sini shibu
2012 International Journal of Information Technology and Computer Science  
T management characteristic itemsets are t specified thre Discovery of process for m rules from da for temporal This make which can gen  ...  T unpredictable as fundamen investors with predicting th discover all th there is a nee deeper kind extensively in forecasting.  ...  The goal of utility mining is to discover all the itemsets whose utility values are beyond a user specified threshold in a transaction database.  ... 
doi:10.5815/ijitcs.2012.04.04 fatcat:gomcziyoajbetmwjejcj7ezwzu

On mining Incremental Databases for Regular and Frequent Patterns

NVS Pavan Kumar, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India
2019 International Journal of Emerging Trends in Engineering Research  
Many applications exist that deal with regular and frequent patterns having negative associations mined from incremental databases.  ...  Many algorithms have been in existence for incremental mining databases to derive frequent patterns that yield positive associations.  ...  INTRODUCTION A database stores the data related to a set of transactions that happen over some time. A database mined at a specific point in time.  ... 
doi:10.30534/ijeter/2019/12792019 fatcat:omobgdpdujc43n3bra7tkhuu6m
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