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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.  ...  In this paper, a systematic literature review has been presented for different algorithms, which are being used for utility itemset mining. 37 studies have been selected to answer the research questions  ...  A systematic review has been done for the structures, advantages, and disadvantages of the algorithms.  ... 
doi:10.47059/revistageintec.v11i3.1959 fatcat:hpbmpkn7mfhjpk6yulsv4cqcoy

Foundations of Crowd Data Sourcing

Yael Amsterdamer, Tova Milo
2015 SIGMOD record  
We also overview a broader spectrum of work on crowd data sourcing, and highlight directions for further research.  ...  In this paper, we review the foundational challenges in modeling crowd-based data sourcing, for its two main tasks, namely, harvesting data and processing it with the help of the crowd.  ...  We also thank the anonymous reviewer for useful comments.  ... 
doi:10.1145/2737817.2737819 fatcat:3wp6ly2dyjeehesdl6mtfirg5q

Data mining for decision support with uncertainty on the airplane

A. Sene, B. Kamsu-Foguem, P. Rumeau
2018 Data & Knowledge Engineering  
A great deal of previous research into uncertainty has focused on other approaches like fuzzy logic [8] . The adequacy of one method or another often depends on the context.  ...  A. Sene).  ...  The authors thank the reviewers who provided valuable comments and suggestions for the content of this article.  ... 
doi:10.1016/j.datak.2018.06.002 fatcat:pd3g75ypbjbbdfildx7giek2ii

A Survey of Utility-Oriented Pattern Mining

Wensheng Gan, Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Vincent Tseng, Philip Yu
2019 IEEE Transactions on Knowledge and Data Engineering  
We conclude our survey with a discussion on open and practical challenges in this field.  ...  A comprehensive review of advanced topics of existing high-utility pattern mining techniques is offered, with a discussion of their pros and cons.  ...  Expected/potential utility determines both uncertainty and utility of a pattern in uncertain data [73] . Thus, for UPM, this measure is suitable for dealing with uncertain data.  ... 
doi:10.1109/tkde.2019.2942594 fatcat:nipxkmyfb5cyxh2662xbz6feo4

Data Mining Application for Finding Patterns: Survey of Large Data Research Tools

Aive Islam
2017 American Journal of Neural Networks and Applications  
Data Mining is now a common method for mining data from databases and finding out patterns from the data. Today many organizations are using data mining techniques.  ...  In this paper concepts and techniques such as Neural Network, Decision Tree, Clustering, Association Rule, Clustering and many more techniques of Data Mining is reviewed.  ...  The downward closure property ensures that all subsets of a frequent itemset must be frequent as well.  ... 
doi:10.11648/j.ajnna.20170302.11 fatcat:mjqek24re5faxbxfax4xgtwebq

Profiling relational data: a survey

Ziawasch Abedjan, Lukasz Golab, Felix Naumann
2015 The VLDB journal  
This survey provides a classification of data profiling tasks and comprehensively reviews the state of the art for each class.  ...  Among the simpler results are statistics, such as the number of null values and distinct values in a column, its data type, or the most frequent patterns of its data values.  ...  In the next iteration, only the frequent itemsets of size one are expanded to find frequent itemsets of size two, and so on.  ... 
doi:10.1007/s00778-015-0389-y fatcat:ojj7blyqgrfrhmyi7yjtn6stia

A Survey on Privacy Preserving Association Rule Mining

Sathiyapriya K, G.Sudha Sadasivam
2013 International Journal of Data Mining & Knowledge Management Process  
Businesses share data, outsourcing for specific business problems. Large companies stake a large part of their business on analysis of private data.  ...  So, it is crucial to reliably protect their data due to legal and customer concerns. In this paper, a review of the state-of-the-art methods for privacy preservation is presented.  ...  These combinations have to show at least a certain frequency and are thus called frequent itemsets. The second step generates rules out of the discovered frequent itemsets.  ... 
doi:10.5121/ijdkp.2013.3208 fatcat:lgfkntvc5ncknnjonmlesn4zpi

Integration of Fuzzy and Deep Learning in Three-Way Decisions

L.D.C.S. Subhashini, Yuefeng Li, Jinglan Zhang, Ajantha S. Atukorale
2020 2020 International Conference on Data Mining Workshops (ICDMW)  
In opinion mining, pattern mining can discover sequencing terms that frequently co-occur in a customer review, and such set of terms can represent the knowledge in reviews effectively.  ...  This review is uncertain as the frequent features can appear in both the negative or positive categories.  ... 
doi:10.1109/icdmw51313.2020.00019 fatcat:5245hd4wrvagdnntwjokulrx6u

ProUM: Projection-based Utility Mining on Sequence Data [article]

Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Han-Chieh Chao, Hamido Fujita, Philip S. Yu
2019 arXiv   pre-print
Utility mining has attracted a great amount of attention, but most of the existing studies have been developed to deal with itemset-based data.  ...  In addition, the mining efficiency of utility mining on sequence data still needs to be improved, especially for long sequences or when there is a low minimum utility threshold.  ...  A great effort has been put forth by the data mining community to discover frequent patterns from itemset-based data, such as Apriori [3] and FP-growth [20] methods.  ... 
arXiv:1904.07764v2 fatcat:e7y2nnnk4rbrrcwtupeizdnple

A Framework for Evaluating Privacy Preserving Data Mining Algorithms*

Elisa Bertino, Igor Nai Fovino, Loredana Parasiliti Provenza
2005 Data mining and knowledge discovery  
Several data mining techniques, incorporating privacy protection mechanisms, have been developed that allow one to hide sensitive itemsets or patterns, before the data mining process is executed.  ...  Recently, a new class of data mining methods, known as privacy preserving data mining (PPDM) algorithms, has been developed by the research community working on security and knowledge discovery.  ...  They focus on hiding a set of frequent patterns, containing highly sensitive knowledge.  ... 
doi:10.1007/s10618-005-0006-6 fatcat:pzxafzivejbchgj2ltx7naxyii

A Weighted Frequent Itemset Mining Algorithm for Intelligent Decision in Smart System

A. Kowsalya, S. Uma Parameswari, N. Kokila
2019 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
Frequent itemset mining, as an imperative of association rule examination, one of the mainly essential study fields in data mining.  ...  Weighted frequent itemset mining in vague databases equally the current prospect and significance of items into version in order to discover frequent itemsets of great importance to users.  ...  Rathod [1] proposed a decremental pruning (DP) approach for efficient mining of frequent itemsets from existential uncertain data.  ... 
doi:10.32628/cseit195518 fatcat:pcomi36l2jem5ldirjhhosuvgm

A Literature Study on Traditional Clustering Algorithms for Uncertain Data

S Sathappan, S Sridhar, D Tomar
2017 British Journal of Mathematics & Computer Science  
Numerous traditional Clustering algorithms for uncertain data have been proposed in the literature such as k-medoid, global kernel k-means, k-mode, u-rule, uk-means algorithm, Uncertainty-Lineage database  ...  In this probabilistic context, an itemset X is called frequent if the probability that X occurs in atleast minSup transactions is above a given threshold ґ.  ...  In consideration of the probabilistic formulations, they present a framework which is able to solve the Probabilistic Frequent Itemset Mining (PFIM) problem efficiently.  ... 
doi:10.9734/bjmcs/2017/32697 fatcat:heafraeutff2vhnomcpbpihs24

On the Positioning and Market Selection of Opera Performance Art Based on Industrial Data Mining

Kaixi Yu, Hyunju Choi, Xin Ning
2022 Wireless Communications and Mobile Computing  
The success of opera performances on the market has a direct impact on whether they can achieve market success and achieve the ultimate goal of maximizing profits.  ...  The opera performance market is maturing, and at the same time, new opera performance and marketing methods are being introduced on a regular basis to meet the growing spiritual needs of the audience.  ...  the mining of frequent itemsets in the first step.  ... 
doi:10.1155/2022/4141355 fatcat:q5c7je2y5jcdjakrkrtjukcbga

A Survey of Parallel Sequential Pattern Mining [article]

Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu
2019 arXiv   pre-print
., frequent itemset mining and association rule mining, and also suffers from the above challenges when handling the large-scale data.  ...  Some advanced topics for PSPM, including parallel quantitative / weighted / utility sequential pattern mining, PSPM from uncertain data and stream data, hardware acceleration for PSPM, are further reviewed  ...  ACKNOWLEDGMENT We would like to thank the anonymous reviewers for their detailed comments and constructive suggestions for this paper.  ... 
arXiv:1805.10515v2 fatcat:6bothuniprd7xclmpwx26s6udu

A Survey of Utility-Oriented Pattern Mining [article]

Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Vincent S. Tseng, Philip S. Yu
2019 arXiv   pre-print
We conclude our survey with a discussion on open and practical challenges in this field.  ...  A comprehensive review of advanced topics of existing high-utility pattern mining techniques is offered, with a discussion of their pros and cons.  ...  Acknowledgment We would like to thank the editors and anonymous reviewers for their detailed comments and constructive suggestions which have improved the quality of this paper.  ... 
arXiv:1805.10511v2 fatcat:gfv2uvkq2vhyrcinpvteqn37su
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