Association Rule Hiding For Data Mining
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Association Rule Hiding For Data Mining
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Author : Aris Gkoulalas-Divanis
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-05-17
Association Rule Hiding For Data Mining written by Aris Gkoulalas-Divanis and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-17 with Computers categories.
Privacy and security risks arising from the application of different data mining techniques to large institutional data repositories have been solely investigated by a new research domain, the so-called privacy preserving data mining. Association rule hiding is a new technique in data mining, which studies the problem of hiding sensitive association rules from within the data. Association Rule Hiding for Data Mining addresses the problem of "hiding" sensitive association rules, and introduces a number of heuristic solutions. Exact solutions of increased time complexity that have been proposed recently are presented, as well as a number of computationally efficient (parallel) approaches that alleviate time complexity problems, along with a thorough discussion regarding closely related problems (inverse frequent item set mining, data reconstruction approaches, etc.). Unsolved problems, future directions and specific examples are provided throughout this book to help the reader study, assimilate and appreciate the important aspects of this challenging problem. Association Rule Hiding for Data Mining is designed for researchers, professors and advanced-level students in computer science studying privacy preserving data mining, association rule mining, and data mining. This book is also suitable for practitioners working in this industry.
Study Of Association Rule Mining And Different Hiding Techniques
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Author :
language : en
Publisher:
Release Date :
Study Of Association Rule Mining And Different Hiding Techniques written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Data mining is the process of extracting hidden patterns from data. As more data is gathered, with the amount of data doubling every three years, data mining is becoming an increasingly important tool to transform this data into information. In this paper, we first focused on APRIORI algorithm, a popular data mining technique and compared the performances of a linked list based implementation as a basis and a tries-based implementation on it for mining frequent item sequences in a transactional database. We examined the data structure, implementation and algorithmic features mainly focusing on those that also arise in frequent item set mining. This algorithm has given us new capabilities to identify associations in large data sets. But a key problem, and still not sufficiently investigated, is the need to balance the confidentiality of the disclosed data with the legitimate needs of the data users. One rule is characterized as sensitive if its disclosure risk is above a certain privacy threshold. Sometimes, sensitive rules should not be disclosed to the public, since among other things, they may be used for inferring sensitive data, or they may provide business competitors with an advantage. So, next we worked with some association rule hiding algorithms and examined their performances in order to analyze their time complexity and the impact that they have in the original database. We worked on two different side effects - one was the number of new rules generated during the hiding process and the other one was the number of non-sensitive rules lost during the process.
Association Rule Mining
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Author : Chengqi Zhang
language : en
Publisher: Springer
Release Date : 2003-08-01
Association Rule Mining written by Chengqi Zhang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-08-01 with Computers categories.
Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professionals, association rule mining is receiving increasing attention. The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.
Rare Association Rule Mining And Knowledge Discovery Technologies For Infrequent And Critical Event Detection
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Author : Koh, Yun Sing
language : en
Publisher: IGI Global
Release Date : 2009-08-31
Rare Association Rule Mining And Knowledge Discovery Technologies For Infrequent And Critical Event Detection written by Koh, Yun Sing and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-31 with Business & Economics categories.
"This book provides readers with an in-depth compendium of current issues, trends, and technologies in association rule mining"--Provided by publisher.
Privacy Preserving Data Mining
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Author : Charu C. Aggarwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-06-10
Privacy Preserving Data Mining written by Charu C. Aggarwal and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-10 with Computers categories.
Advances in hardware technology have increased the capability to store and record personal data. This has caused concerns that personal data may be abused. This book proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions of a particular topic in privacy. The book is designed for researchers, professors, and advanced-level students in computer science, but is also suitable for practitioners in industry.
Post Mining Of Association Rules Techniques For Effective Knowledge Extraction
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Author : Zhao, Yanchang
language : en
Publisher: IGI Global
Release Date : 2009-05-31
Post Mining Of Association Rules Techniques For Effective Knowledge Extraction written by Zhao, Yanchang and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-31 with Computers categories.
Provides a systematic collection on post-mining, summarization and presentation of association rules, and new forms of association rules.
Research Anthology On Privatizing And Securing Data
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2021-04-23
Research Anthology On Privatizing And Securing Data written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-23 with Computers categories.
With the immense amount of data that is now available online, security concerns have been an issue from the start, and have grown as new technologies are increasingly integrated in data collection, storage, and transmission. Online cyber threats, cyber terrorism, hacking, and other cybercrimes have begun to take advantage of this information that can be easily accessed if not properly handled. New privacy and security measures have been developed to address this cause for concern and have become an essential area of research within the past few years and into the foreseeable future. The ways in which data is secured and privatized should be discussed in terms of the technologies being used, the methods and models for security that have been developed, and the ways in which risks can be detected, analyzed, and mitigated. The Research Anthology on Privatizing and Securing Data reveals the latest tools and technologies for privatizing and securing data across different technologies and industries. It takes a deeper dive into both risk detection and mitigation, including an analysis of cybercrimes and cyber threats, along with a sharper focus on the technologies and methods being actively implemented and utilized to secure data online. Highlighted topics include information governance and privacy, cybersecurity, data protection, challenges in big data, security threats, and more. This book is essential for data analysts, cybersecurity professionals, data scientists, security analysts, IT specialists, practitioners, researchers, academicians, and students interested in the latest trends and technologies for privatizing and securing data.
Data Mining
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Author : Dr. Suneel Pappala
language : en
Publisher: Blue Rose Publishers
Release Date : 2022-08-25
Data Mining written by Dr. Suneel Pappala and has been published by Blue Rose Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-25 with Computers categories.
DATA MINING IS USE TO COMPUTER SCIENCE AND ENGINEERING AND INFORMATION TECHNOLOGY STUDENTS. Data Mining is The process of automatically discovering useful information in large data repositories. – Observation = case, record, instance – Variable = field, attribute – Analysis of dependence vs interdependence = Supervised vs unsupervised learning – Relationship = association, concept – Dependent variable Data Mining is mainly concentrated on Association rule, Mining Frequent Patterns it is concentrated on Associations and correlations and also concentrated on Mining Methods,Mining Various kinds of Association Rules,Correlation Analysis, Constraint based Association mining. Graph Pattern Mining SPM. Classification and Prediction ,Basic concepts,Decision tree induction,Bayesian classification, Rule–based classification, Lazy learner. Cluster analysis,Types of Data in Cluster Analysis,Categorization of Major Clustering Methods, Partitioning Methods, Hierarchical Methods,Density Based Methods, Grid Based Methods, Outlier Analysis. Basic concepts in Mining data streams Mining Time series data Mining sequence patterns in Transactional databases Mining Object Spatial Multimedia Text and Web data Spatial Data mining Multimedia Data mining Text Mining Mining the World Wide Web.
Advances In Data Mining Applications And Theoretical Aspects
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Author : Petra Perner
language : en
Publisher: Springer
Release Date : 2016-06-27
Advances In Data Mining Applications And Theoretical Aspects written by Petra Perner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-27 with Computers categories.
This book constitutes the refereed proceedings of the 16th Industrial Conference on Advances in Data Mining, ICDM 2016, held in New York, NY, USA, in July 2016. The 33 revised full papers presented were carefully reviewed and selected from 100 submissions. The topics range from theoretical aspects of data mining to applications of data mining, such as in multimedia data, in marketing, in medicine, and in process control, industry, and society.
Designing A Multi Level Support Based Association Mining Algorithm
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Author : Shanmuganathan Vasanthapriyan
language : en
Publisher: Lulu.com
Release Date : 2014-09-29
Designing A Multi Level Support Based Association Mining Algorithm written by Shanmuganathan Vasanthapriyan and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-29 with Business & Economics categories.
Finding of hidden and previously unknown information in large collection of data is the process of data mining. Mining association rules is a very important model in data mining. Using association rules different type of regularities and patterns can be identified. The main approach of association rules is the market basket analysis which exposes relationships between the items customers are regularly buying. In most of the previous approaches of finding association rules a single minimum support threshold value is used for all the items or itemsets. But all the items in an itemset do not behave in the same way where some appear very frequently and some appear very rarely. Therefore the support requirements should vary with different items. Here we proposed new algorithm and was tested using different data sets to prove the advantages. The analysis showed that the proposed algorithm is easy and efficient and it saves time by focusing only on necessary associations comparing to existing algorithms.