Association Rules
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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.
Data Mining For Association Rules And Sequential Patterns
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Author : Jean-Marc Adamo
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Data Mining For Association Rules And Sequential Patterns written by Jean-Marc Adamo 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 2012-12-06 with Computers categories.
Recent advances in data collection, storage technologies, and computing power have made it possible for companies, government agencies and scientific laboratories to keep and manipulate vast amounts of data relating to their activities. This state-of-the-art monograph discusses essential algorithms for sophisticated data mining methods used with large-scale databases, focusing on two key topics: association rules and sequential pattern discovery. This will be an essential book for practitioners and professionals in computer science and computer engineering.
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.
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.
Objects Of Association Rules And Bye Laws Etc
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Author : Manchester, Salford and District Licensed Victuallers' Association (MANCHESTER)
language : en
Publisher:
Release Date : 1904
Objects Of Association Rules And Bye Laws Etc written by Manchester, Salford and District Licensed Victuallers' Association (MANCHESTER) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1904 with categories.
Association Rule Hiding For Data Mining
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Author : Aris Gkoulalas-Divanis
language : en
Publisher: Springer
Release Date : 2010-05-27
Association Rule Hiding For Data Mining written by Aris Gkoulalas-Divanis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-27 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.
Observational Calculi And Association Rules
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Author : Jan Rauch
language : en
Publisher: Springer
Release Date : 2012-12-25
Observational Calculi And Association Rules written by Jan Rauch and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-25 with Technology & Engineering categories.
Observational calculi were introduced in the 1960’s as a tool of logic of discovery. Formulas of observational calculi correspond to assertions on analysed data. Truthfulness of suitable assertions can lead to acceptance of new scientific hypotheses. The general goal was to automate the process of discovery of scientific knowledge using mathematical logic and statistics. The GUHA method for producing true formulas of observational calculi relevant to the given problem of scientific discovery was developed. Theoretically interesting and practically important results on observational calculi were achieved. Special attention was paid to formulas - couples of Boolean attributes derived from columns of the analysed data matrix. Association rules introduced in the 1990’s can be seen as a special case of such formulas. New results on logical calculi and association rules were achieved. They can be seen as a logic of association rules. This can contribute to solving contemporary challenging problems of data mining research and practice. The book covers thoroughly the logic of association rules and puts it into the context of current research in data mining. Examples of applications of theoretical results to real problems are presented. New open problems and challenges are listed. Overall, the book is a valuable source of information for researchers as well as for teachers and students interested in data mining.
Association Rule Mining
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Author : Chengqi Zhang
language : en
Publisher:
Release Date : 2014-01-15
Association Rule Mining written by Chengqi Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Discovering Of Association Rules Without A Minimum Support Threshold Coherent Rules Discovery
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Author : Alex Tze Hiang Sim
language : en
Publisher:
Release Date : 2009
Discovering Of Association Rules Without A Minimum Support Threshold Coherent Rules Discovery written by Alex Tze Hiang Sim and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Association rule mining categories.
An algorithm to discover coherent rules is also presented in this thesis. The algorithm was designed to find the shortest and strongest rule or most effectual coherent rules by exploiting the properties of coherent rules. Decision or actions can be implemented based on these coherent rules. In a situation whereby users are interested in weaker and/or longer rules, the algorithm enables parameters to be set. Unlike support threshold settings, these parameters do not require users to have prior knowledge of the context in which the data mining takes place. We have tested our framework on several datasets. The results confirm the strength of coherent rules in finding association rules that can be reasoned logically and in finding association rules that consider both infrequent items and negative associations. The algorithm used to discover coherent rules is also efficient. This was demonstrated by the number of prunings made to the search space during the discovery process. This study suggests that our framework for discovering coherent rules offers a technique for data mining that overcomes the limitations associated with existing methods and enables the finding of association rules among the presence and/or absence of a set of items without a preset minimum support threshold. The results justify continuing research in this area in order to increase the body of scientific knowledge of data mining - and specifically, association rules - and to provide practical support to those involved in data mining activities.
Lecture Notes In Data Mining
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Author : Michael W. Berry
language : en
Publisher: World Scientific
Release Date : 2006
Lecture Notes In Data Mining written by Michael W. Berry and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computers categories.
The continual explosion of information technology and the need for better data collection and management methods has made data mining an even more relevant topic of study. Books on data mining tend to be either broad and introductory or focus on some very specific technical aspect of the field. This book is a series of seventeen edited OC student-authored lecturesOCO which explore in depth the core of data mining (classification, clustering and association rules) by offering overviews that include both analysis and insight. The initial chapters lay a framework of data mining techniques by explaining some of the basics such as applications of Bayes Theorem, similarity measures, and decision trees. Before focusing on the pillars of classification, clustering and association rules, the book also considers alternative candidates such as point estimation and genetic algorithms. The book''s discussion of classification includes an introduction to decision tree algorithms, rule-based algorithms (a popular alternative to decision trees) and distance-based algorithms. Five of the lecture-chapters are devoted to the concept of clustering or unsupervised classification. The functionality of hierarchical and partitional clustering algorithms is also covered as well as the efficient and scalable clustering algorithms used in large databases. The concept of association rules in terms of basic algorithms, parallel and distributive algorithms and advanced measures that help determine the value of association rules are discussed. The final chapter discusses algorithms for spatial data mining. Sample Chapter(s). Chapter 1: Point Estimation Algorithms (397 KB). Contents: Point Estimation Algorithms; Applications of Bayes Theorem; Similarity Measures; Decision Trees; Genetic Algorithms; Classification: Distance Based Algorithms; Decision Tree-Based Algorithms; Covering (Rule-Based) Algorithms; Clustering: An Overview; Clustering Hierarchical Algorithms; Clustering Partitional Algorithms; Clustering: Large Databases; Clustering Categorical Attributes; Association Rules: An Overview; Association Rules: Parallel and Distributed Algorithms; Association Rules: Advanced Techniques and Measures; Spatial Mining: Techniques and Algorithms. Readership: An introductory data mining textbook or a technical data mining book for an upper level undergraduate or graduate level course."