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Inhibitory Rules In Data Analysis
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Book Synopsis Inhibitory Rules in Data Analysis by : Pawel Delimata
Download or read book Inhibitory Rules in Data Analysis written by Pawel Delimata and published by Springer Science & Business Media. This book was released on 2008-10-01 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is devoted to theoretical and experimental study of inhibitory decision and association rules. Inhibitory rules contain on the right-hand side a relation of the kind “attribut = value”. The use of inhibitory rules instead of deterministic (standard) ones allows us to describe more completely infor- tion encoded in decision or information systems and to design classi?ers of high quality. The mostimportantfeatureofthis monographis thatit includesanadvanced mathematical analysis of problems on inhibitory rules. We consider algorithms for construction of inhibitory rules, bounds on minimal complexity of inhibitory rules, and algorithms for construction of the set of all minimal inhibitory rules. We also discuss results of experiments with standard and lazy classi?ers based on inhibitory rules. These results show that inhibitory decision and association rules can be used in data mining and knowledge discovery both for knowledge representation and for prediction. Inhibitory rules can be also used under the analysis and design of concurrent systems. The results obtained in the monograph can be useful for researchers in such areas as machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory, and logical analysis of data (LAD). The monograph can be used under the creation of courses for graduate students and for Ph.D. studies. TheauthorsofthisbookextendanexpressionofgratitudetoProfessorJanusz Kacprzyk, to Dr. Thomas Ditzinger and to the Studies in Computational Int- ligence sta? at Springer for their support in making this book possible.
Book Synopsis Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions by : Fawaz Alsolami
Download or read book Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions written by Fawaz Alsolami and published by Springer. This book was released on 2019-03-13 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: The results presented here (including the assessment of a new tool – inhibitory trees) offer valuable tools for researchers in the areas of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions. The authors consider various examples of problems and corresponding decision tables with many-valued decisions, discuss the difference between decision and inhibitory trees and rules, and develop tools for their analysis and design. Applications include the study of totally optimal (optimal in relation to a number of criteria simultaneously) decision and inhibitory trees and rules; the comparison of greedy heuristics for tree and rule construction as single-criterion and bi-criteria optimization algorithms; and the development of a restricted multi-pruning approach used in classification and knowledge representation.
Book Synopsis Beyond Databases, Architectures and Structures by : Stanisław Kozielski
Download or read book Beyond Databases, Architectures and Structures written by Stanisław Kozielski and published by Springer. This book was released on 2015-04-28 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th International Conference entitled Beyond Databases, Architectures and Structures, BDAS 2015, held in Ustroń, Poland, in May 2015. This book consists of 53 carefully revised selected papers that are assigned to 8 thematic groups: database architectures and performance; data integration, storage and data warehousing; ontologies and semantic web; artificial intelligence, data mining and knowledge discovery; image analysis and multimedia mining; spatial data analysis; database systems development; application of database systems.
Book Synopsis Three Approaches to Data Analysis by : Igor Chikalov
Download or read book Three Approaches to Data Analysis written by Igor Chikalov and published by Springer Science & Business Media. This book was released on 2012-07-28 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the following three approaches to data analysis are presented: - Test Theory, founded by Sergei V. Yablonskii (1924-1998); the first publications appeared in 1955 and 1958, - Rough Sets, founded by Zdzisław I. Pawlak (1926-2006); the first publications appeared in 1981 and 1982, - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. - Logical Analysis of Data, founded by Peter L. Hammer (1936-2006); the first publications appeared in 1986 and 1988. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected. These three approaches have much in common, but researchers active in one of these areas often have a limited knowledge about the results and methods developed in the other two. On the other hand, each of the approaches shows some originality and we believe that the exchange of knowledge can stimulate further development of each of them. This can lead to new theoretical results and real-life applications and, in particular, new results based on combination of these three data analysis approaches can be expected.
Book Synopsis Rough Set Theory: A True Landmark in Data Analysis by : Ajith Abraham
Download or read book Rough Set Theory: A True Landmark in Data Analysis written by Ajith Abraham and published by Springer Science & Business Media. This book was released on 2009-02-26 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part 1 of this book deals with theoretical contributions of rough set theory, and parts 2 and 3 focus on several real world data mining applications. The book thoroughly explores recent results in rough set research.
Book Synopsis Transactions on Rough Sets XII by : Roman Slowiński
Download or read book Transactions on Rough Sets XII written by Roman Slowiński and published by Springer. This book was released on 2010-07-27 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains revised papers from the Rough Set and Knowledge Technology Conference (RSKT 2008), together with five papers introducing advances in rough set theory and its applications. It is part of the LNCS Transactions on Rough Sets series.
Book Synopsis Pattern Recognition And Big Data by : Pal Sankar Kumar
Download or read book Pattern Recognition And Big Data written by Pal Sankar Kumar and published by World Scientific. This book was released on 2016-12-15 with total page 876 pages. Available in PDF, EPUB and Kindle. Book excerpt: Containing twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications. Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis.
Download or read book Transactions on Rough Sets XI written by and published by Springer. This book was released on 2010-01-10 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume XI of the Transactions on Rough Sets (TRS) provides evidence of f- ther growth in the rough set landscape, both in terms of its foundations and applications. This volume provides further evidence of the number of research streams that were either directly or indirectly initiated by the seminal work on rough 1 sets by Zdzis law Pawlak (1926-2006) . Evidence of the growth of various rough 2 set-based research streams can be found in the rough set database . Thisvolumecontainsarticlesintroducingadvancesinthefoundationsand- plicationsofroughsets.These advancesinclude: calculusofattribute-value pairs useful in mining numerical data, de?nability and coalescence of approximations, variable consistency generalization approach to bagging controlled by measures of consistency, classical and dominance-based rough sets in the search for genes, judgementaboutsatis?abilityunderincompleteinformation,irreducibledescr- tive sets of attributes for information systems useful in the design of concurrent data models, computational theory of perceptions (CTP) and its characteristics and the relation with fuzzy-granulation, methods and algorithms of the Net- TRS system, a recursive version of the apriori algorithm designed for parallel processing, and decision table reduction method based on fuzzy rough sets. Theeditorsandauthorsofthisvolumeextendtheirgratitudetothereviewers of articles in this volume, Alfred Hofmann, Ursula Barth, Christine Reiss and the LNCS sta? at Springer for their support in making this volume of the TRS possible.
Book Synopsis Beyond Databases, Architectures, and Structures by : Stanislaw Kozielski
Download or read book Beyond Databases, Architectures, and Structures written by Stanislaw Kozielski and published by Springer. This book was released on 2014-04-18 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th IEEE International Conference Beyond Databases, Architectures, and Structures, BDAS 2014, held in Ustron, Poland, in May 2014. This book consists of 56 carefully revised selected papers that are assigned to 11 thematic groups: query languages, transactions and query optimization; data warehousing and big data; ontologies and semantic web; computational intelligence and data mining; collective intelligence, scheduling, and parallel processing; bioinformatics and biological data analysis; image analysis and multimedia mining; security of database systems; spatial data analysis; applications of database systems; Web and XML in database systems.
Book Synopsis Rough Sets, Fuzzy Sets, Data Mining and Granular Computing by : Hiroshi Sakai
Download or read book Rough Sets, Fuzzy Sets, Data Mining and Granular Computing written by Hiroshi Sakai and published by Springer. This book was released on 2009-12-15 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2009, held in Delhi, India in December 2009 in conjunction with the Third International Conference on Pattern Recognition and Machine Intelligence, PReMI 2009. RSFDGrC 2009 is the core component of a broader Rough Set Year in India initiative, RSIndia09. The 56 revised full papers presented together with 6 invited papers and a report on the Rough Set Year in India 2009 project were carefully reviewed and selected from a total of 130 submissions. The papers are organized in topical sections on foundations of rough sets and beyond; rought set algorithms and applications; fuzzy set foundations and applications; data mining and knowledge discovery; clustering and current trends in computing; and information retrieval and text mining.
Book Synopsis Rough Set and Knowledge Technology by : JingTao Yao
Download or read book Rough Set and Knowledge Technology written by JingTao Yao and published by Springer Science & Business Media. This book was released on 2011-09-21 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Rough Sets and Knowledge Technology, RSKT 2011, held in Banff, Canada, in September 2011. The 89 revised full papers presented together with 3 keynote lectures and 1 invited tutorial session were carefully reviewed and selected from 229 submissions. The papers are organized in topical sections on attribute reduction and feature selection, generalized rough set models, machine learning with rough and hybrid techniques, knowledge technology and intelligent systems and applications.
Book Synopsis Mining Complex Data by : Djamel A. Zighed
Download or read book Mining Complex Data written by Djamel A. Zighed and published by Springer. This book was released on 2008-10-10 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to gather the most recent works that address issues related to the concept of mining complex data. The whole knowledge discovery process being involved, our goal is to provide researchers dealing with each step of this process by key entries. Actually, managing complex data within the KDD process implies to work on every step, starting from the pre-processing (e.g. structuring and organizing) to the visualization and interpretation (e.g. sorting or filtering) of the results, via the data mining methods themselves (e.g. classification, clustering, frequent patterns extraction, etc.). The papers presented here are selected from the workshop papers held yearly since 2006.
Book Synopsis Rough Sets and Current Trends in Computing by : Chien-Chung Chan
Download or read book Rough Sets and Current Trends in Computing written by Chien-Chung Chan and published by Springer. This book was released on 2008-10-16 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: The articles in this volume were selected for presentation at the Sixth Inter- tional Conference on Rough Sets and Current Trends in Computing (RSCTC 2008), which took place on October 23–25 in Akron, Ohio, USA. The conference is a premier event for researchersand industrial professionals interested in the theory and applications of rough sets and related methodo- gies. Since its introduction over 25 years ago by Zdzislaw Pawlak, the theory of rough sets has grown internationally and matured, leading to novel applications and theoretical works in areas such as data mining and knowledge discovery, machine learning, neural nets, granular and soft computing, Web intelligence, pattern recognition and control. The proceedings of the conferences in this - ries, as well as in Rough Sets and Knowledge Technology (RSKT), and the Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC) series report a variety of innovative applications of rough set theory and of its extensions. Since its inception, the mathematical rough set theory was closely connected to application ?elds of computer science and to other areas, such as medicine, which provided additional motivation for its further development and tested its real-life value. Consequently, rough set conferences emphasize the - teractionsandinterconnectionswith relatedresearchareas,providingforumsfor exchanging ideas and mutual learning. The latter aspect is particularly imp- tant since the development of rough set-related applications usually requires a combination of often diverse expertise in rough sets and an application ?eld.
Book Synopsis Computational Intelligence for Knowledge-Based System Design by : Eyke Hüllermeier
Download or read book Computational Intelligence for Knowledge-Based System Design written by Eyke Hüllermeier and published by Springer. This book was released on 2010-06-30 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book constitutes the refereed proceedings of the 13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2010, held in Dortmund, Germany from June 28 - July 2, 2010. The 77 revised full papers were carefully reviewed and selected from 320 submissions and reflect the richness of research in the field of Computational Intelligence and represent developments on topics as: machine learning, data mining, pattern recognition, uncertainty handling, aggregation and fusion of information as well as logic and knowledge processing.
Book Synopsis Transactions on Rough Sets XV by : James F. Peters
Download or read book Transactions on Rough Sets XV written by James F. Peters and published by Springer. This book was released on 2012-07-09 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XV offers a number of research streams that have grown out of the seminal work by Zdzislaw Pawlak. The 4 contributions included in this volume presents a rough set approach in machine learning; the introduction of multi-valued near set theory; the advent of a complete system that supports a rough-near set approach to digital image analysis; and an exhaustive study of the mathematics of vagueness.
Book Synopsis Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018 by : Aboul Ella Hassanien
Download or read book Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018 written by Aboul Ella Hassanien and published by Springer. This book was released on 2018-08-28 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 4th International Conference on Advanced Intelligent Systems and Informatics 2018 (AISI2018), which took place in Cairo, Egypt from September 1 to 3, 2018. This international and interdisciplinary conference, which highlighted essential research and developments in the field of informatics and intelligent systems, was organized by the Scientific Research Group in Egypt (SRGE). The book is divided into several main sections: Intelligent Systems; Robot Modeling and Control Systems; Intelligent Robotics Systems; Machine Learning Methodology and Applications; Sentiment Analysis and Arabic Text Mining; Swarm Optimizations and Applications; Deep Learning and Cloud Computing; Information Security, Hiding, and Biometric Recognition; and Data Mining, Visualization and E-learning.
Book Synopsis Innovative Applications in Data Mining by : Nadia Nedjah
Download or read book Innovative Applications in Data Mining written by Nadia Nedjah and published by Springer Science & Business Media. This book was released on 2009-01-17 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining consists of attempting to discover novel and useful knowledge from data, trying to find patterns among datasets that can help in intelligent decision making. However, reports of real-world case studies are not generally detailed in the literature, due to the fact that they are usually based on proprietary datasets, making it impossible to publish the results. This kind of situation makes hard to evaluate, in a precise way, the degree of effectiveness of data mining techniques in real-world applications. On the other hand, researchers of this field of expertise usually exploit public-domain datasets. This volume offers a wide spectrum of research work developed for data mining for real-world application. In the following, we give a brief introduction of the chapters that are included in this book.
