Heuristic And Optimization For Knowledge Discovery

Author : Abbass, Hussein A.,Newton, Charles S.,Sarker, Ruhul
Publisher : IGI Global
Page : 296 pages
File Size : 46,8 Mb
Release : 2001-07-01
Category : Computers
ISBN : 9781591400172

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Heuristic and Optimization for Knowledge Discovery by Abbass, Hussein A.,Newton, Charles S.,Sarker, Ruhul Pdf

With the large amount of data stored by many organizations, capitalists have observed that this information is an intangible asset. Unfortunately, handling large databases is a very complex process and traditional learning techniques are expensive to use. Heuristic techniques provide much help in this arena, although little is known about heuristic techniques. Heuristic and Optimization for Knowledge Discovery addresses the foundation of this topic, as well as its practical uses, and aims to fill in the gap that exists in current literature.

Author : Ruhul A. Sarker
Publisher : Unknown
Page : 128 pages
File Size : 47,6 Mb
Release : 2002
Category : Combinatorial optimization
ISBN : OCLC:300210136

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Heuristic and Optimization for Knowledge Discovery by Ruhul A. Sarker Pdf

Author : Clarisse Dhaenens,Laetitia Jourdan
Publisher : John Wiley & Sons
Page : 212 pages
File Size : 45,6 Mb
Release : 2016-08-16
Category : Computers
ISBN : 9781119347583

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Metaheuristics for Big Data by Clarisse Dhaenens,Laetitia Jourdan Pdf

Big Data is a new field, with many technological challenges to be understood in order to use it to its full potential. These challenges arise at all stages of working with Big Data, beginning with data generation and acquisition. The storage and management phase presents two critical challenges: infrastructure, for storage and transportation, and conceptual models. Finally, to extract meaning from Big Data requires complex analysis. Here the authors propose using metaheuristics as a solution to these challenges; they are first able to deal with large size problems and secondly flexible and therefore easily adaptable to different types of data and different contexts. The use of metaheuristics to overcome some of these data mining challenges is introduced and justified in the first part of the book, alongside a specific protocol for the performance evaluation of algorithms. An introduction to metaheuristics follows. The second part of the book details a number of data mining tasks, including clustering, association rules, supervised classification and feature selection, before explaining how metaheuristics can be used to deal with them. This book is designed to be self-contained, so that readers can understand all of the concepts discussed within it, and to provide an overview of recent applications of metaheuristics to knowledge discovery problems in the context of Big Data.

Author : Abbass, Hussein A.,Sarker, Ruhul,Newton, Charles S.
Publisher : IGI Global
Page : 310 pages
File Size : 54,6 Mb
Release : 2001-07-01
Category : Computers
ISBN : 9781591400110

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Data Mining: A Heuristic Approach by Abbass, Hussein A.,Sarker, Ruhul,Newton, Charles S. Pdf

Real life problems are known to be messy, dynamic and multi-objective, and involve high levels of uncertainty and constraints. Because traditional problem-solving methods are no longer capable of handling this level of complexity, heuristic search methods have attracted increasing attention in recent years for solving such problems. Inspired by nature, biology, statistical mechanics, physics and neuroscience, heuristics techniques are used to solve many problems where traditional methods have failed. Data Mining: A Heuristic Approach will be a repository for the applications of these techniques in the area of data mining.

Author : Qing Duan,Krishnendu Chakrabarty,Jun Zeng
Publisher : Springer
Page : 160 pages
File Size : 50,7 Mb
Release : 2015-06-13
Category : Technology & Engineering
ISBN : 9783319187389

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Data-Driven Optimization and Knowledge Discovery for an Enterprise Information System by Qing Duan,Krishnendu Chakrabarty,Jun Zeng Pdf

This book provides a comprehensive set of optimization and prediction techniques for an enterprise information system. Readers with a background in operations research, system engineering, statistics, or data analytics can use this book as a reference to derive insight from data and use this knowledge as guidance for production management. The authors identify the key challenges in enterprise information management and present results that have emerged from leading-edge research in this domain. Coverage includes topics ranging from task scheduling and resource allocation, to workflow optimization, process time and status prediction, order admission policies optimization, and enterprise service-level performance analysis and prediction. With its emphasis on the above topics, this book provides an in-depth look at enterprise information management solutions that are needed for greater automation and reconfigurability-based fault tolerance, as well as to obtain data-driven recommendations for effective decision-making.

Author : Thomas Stützle
Publisher : Springer Science & Business Media
Page : 284 pages
File Size : 52,7 Mb
Release : 2009-12-09
Category : Computers
ISBN : 9783642111686

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Learning and Intelligent Optimization: Designing, Implementing and Analyzing Effective Heuristics by Thomas Stützle Pdf

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Learning and Intelligent Optimization, LION 2009 III, held in Trento, Italy, in January 2009. The 15 revised full papers, one extended abstract and two poster sessions were carefully reviewed and selected from 86 submissions for inclusion in the book. The papers cover current issues of stochastic local search methods and meta-heuristics, hybridizations of constraint and mathematical programming with meta-heuristics, supervised, unsupervised and reinforcement learning applied to heuristic search, reactive search (online self-tuning methods), algorithm portfolios and off-line tuning methods, algorithms for dynamic, stochastic and multi-objective problems, interface(s) between discrete and continuous optimization, experimental analysis and modeling of algorithms, theoretical foundations, parallelization of optimization algorithms, memory-based optimization, prohibition-based methods (tabu search), memetic algorithms, evolutionary algorithms, dynamic local search, iterated local search, variable neighborhood search and swarm intelligence methods (ant colony optimization, particle swarm optimization etc.).

Author : Fabrice Guillet,Gilbert Ritschard,Djamel Abdelkader Zighed
Publisher : Springer
Page : 244 pages
File Size : 47,7 Mb
Release : 2012-02-09
Category : Technology & Engineering
ISBN : 9783642258381

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Advances in Knowledge Discovery and Management by Fabrice Guillet,Gilbert Ritschard,Djamel Abdelkader Zighed Pdf

During the last decade, Knowledge Discovery and Management (KDM or, in French, EGC for Extraction et Gestion des connaissances) has been an intensive and fruitful research topic in the French-speaking scientific community. In 2003, this enthusiasm for KDM led to the foundation of a specific French-speaking association, called EGC, dedicated to supporting and promoting this topic. More precisely, KDM is concerned with the interface between knowledge and data such as, among other things, Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and Semantic Web. The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC 2010 Conference held in Tunis, Tunisia in January 2010. The volume is organized in three parts. Part I includes four chapters concerned with various aspects of Data Cube and Ontology-based representations. Part II is composed of four chapters concerned with Efficient Pattern Mining issues, while in Part III the last four chapters address Data Preprocessing and Information Retrieval.

Author : Massih-Reza Amini,Stéphane Canu,Asja Fischer,Tias Guns,Petra Kralj Novak,Grigorios Tsoumakas
Publisher : Springer Nature
Page : 669 pages
File Size : 41,9 Mb
Release : 2023-03-16
Category : Computers
ISBN : 9783031264191

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Machine Learning and Knowledge Discovery in Databases by Massih-Reza Amini,Stéphane Canu,Asja Fischer,Tias Guns,Petra Kralj Novak,Grigorios Tsoumakas Pdf

The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; . Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.

Author : Alípio Jorge,Luís Torgo,Pavel Brazdil,Rui Camacho,João Gama
Publisher : Springer
Page : 719 pages
File Size : 46,5 Mb
Release : 2005-11-07
Category : Computers
ISBN : 9783540316657

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Knowledge Discovery in Databases: PKDD 2005 by Alípio Jorge,Luís Torgo,Pavel Brazdil,Rui Camacho,João Gama Pdf

The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the ?fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004), Porto received the 16th edition of ECML and the 9th PKDD in October 3–7. Having the two conferences together seems to be working well: 585 di?erent paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scienti?c work required a tremendous e?ort from Area Chairs, Program Committee members and some additional reviewers. On average, PC members had 10 papers to evaluate, and Area Chairs had 25 papers to decide upon. We managed to have 3 highly qua- ?edindependentreviewsperpaper(withveryfewexceptions)andoneadditional overall input from one of the Area Chairs. After the authors’ responses and the online discussions for many of the papers, we arrived at the ?nal selection of 40 regular papers for ECML and 35 for PKDD. Besides these, 32 others were accepted as short papers for ECML and 35 for PKDD. This represents a joint acceptance rate of around 13% for regular papers and 25% overall. We thank all involved for all the e?ort with reviewing and selection of papers. Besidesthecoretechnicalprogram,ECMLandPKDDhad6invitedspeakers, 10 workshops, 8 tutorials and a Knowledge Discovery Challenge.

Author : Dinh Phung,Vincent S. Tseng,Geoffrey I. Webb,Bao Ho,Mohadeseh Ganji,Lida Rashidi
Publisher : Springer
Page : 852 pages
File Size : 54,5 Mb
Release : 2018-06-16
Category : Computers
ISBN : 9783319930404

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Advances in Knowledge Discovery and Data Mining by Dinh Phung,Vincent S. Tseng,Geoffrey I. Webb,Bao Ho,Mohadeseh Ganji,Lida Rashidi Pdf

This three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on new ideas, original research results and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems and the emerging applications.

Author : Evangelos Triantaphyllou,Giovanni Felici
Publisher : Springer
Page : 0 pages
File Size : 42,6 Mb
Release : 2011-02-11
Category : Computers
ISBN : 1441941738

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Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques by Evangelos Triantaphyllou,Giovanni Felici Pdf

This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications. Most theoretical developments are accompanied by extensive empirical analysis, offering a deep insight into both theoretical and practical aspects of the subject. The book presents the combined research experiences of 40 expert contributors of world renown.

Author : Swayze, Susan
Publisher : IGI Global
Page : 198 pages
File Size : 54,6 Mb
Release : 2020-06-26
Category : Computers
ISBN : 9781799822370

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Optimizing Data and New Methods for Efficient Knowledge Discovery and Information Resources Management: Emerging Research and Opportunities by Swayze, Susan Pdf

The fast-paced world created by the accessibility of consumer information through internet-generated data requires improved information-management platforms. The continuous evaluation and evolution of these systems facilitate enhanced data reference and output. Optimizing Data and New Methods for Efficient Knowledge Discovery and Information Resources Management is a critical research publication that provides insight into the varied and rapidly changing fields of knowledge discovery and information resource management. Highlighting a range of topics such as datamining, artificial intelligence, and risk assessment, this book is essential for librarians, academicians, policymakers, information managers, professionals, and researchers in fields that include artificial intelligence, knowledge discovery, data visualization, big data, and information resources management.

Author : Farouk Yalaoui,Lionel Amodeo,El-Ghazali Talbi
Publisher : Springer Nature
Page : 444 pages
File Size : 55,8 Mb
Release : 2020-12-15
Category : Technology & Engineering
ISBN : 9783030589301

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Heuristics for Optimization and Learning by Farouk Yalaoui,Lionel Amodeo,El-Ghazali Talbi Pdf

This book is a new contribution aiming to give some last research findings in the field of optimization and computing. This work is in the same field target than our two previous books published: “Recent Developments in Metaheuristics” and “Metaheuristics for Production Systems”, books in Springer Series in Operations Research/Computer Science Interfaces. The challenge with this work is to gather the main contribution in three fields, optimization technique for production decision, general development for optimization and computing method and wider spread applications. The number of researches dealing with decision maker tool and optimization method grows very quickly these last years and in a large number of fields. We may be able to read nice and worthy works from research developed in chemical, mechanical, computing, automotive and many other fields.

Author : Gregory Piatetsky-Shapiro,William Frawley
Publisher : MIT Press
Page : 550 pages
File Size : 54,8 Mb
Release : 1991
Category : Computers
ISBN : UOM:39015025010748

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Knowledge Discovery in Databases by Gregory Piatetsky-Shapiro,William Frawley Pdf

Knowledge Discovery in Databases brings together current research on the exciting problem of discovering useful and interesting knowledge in databases. It spans many different approaches to discovery, including inductive learning, bayesian statistics, semantic query optimization, knowledge acquisition for expert systems, information theory, and fuzzy 1 sets.The rapid growth in the number and size of databases creates a need for tools and techniques for intelligent data understanding. Relationships and patterns in data may enable a manufacturer to discover the cause of a persistent disk failure or the reason for consumer complaints. But today's databases hide their secrets beneath a cover of overwhelming detail. The task of uncovering these secrets is called discovery in databases. This loosely defined subfield of machine learning is concerned with discovery from large amounts of possible uncertain data. Its techniques range from statistics to the use of domain knowledge to control search.Following an overview of knowledge discovery in databases, thirty technical chapters are grouped in seven parts which cover discovery of quantitative laws, discovery of qualitative laws, using knowledge in discovery, data summarization, domain specific discovery methods, integrated and multi-paradigm systems, and methodology and application issues. An important thread running through the collection is reliance on domain knowledge, starting with general methods and progressing to specialized methods where domain knowledge is built in. Gregory Piatetski-Shapiro is Senior Member of Technical Staff and Principal Investigator of the Knowledge Discovery Project at GTE Laboratories. William Frawley is Principal Member of Technical Staff at GTE and Principal Investigator of the Learning in Expert Domains Project.

Author : Yong Liu,Lipo Wang,Liang Zhao,Zhengtao Yu
Publisher : Springer Nature
Page : 1004 pages
File Size : 54,5 Mb
Release : 2019-11-06
Category : Technology & Engineering
ISBN : 9783030324568

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Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery by Yong Liu,Lipo Wang,Liang Zhao,Zhengtao Yu Pdf

This book discusses the recent advances in natural computation, fuzzy systems and knowledge discovery. Presenting selected, peer-reviewed papers from the 15th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2019), held in Kunming, China, from 20 to 22 July 2019, it is a useful resource for researchers, including professors and graduate students, as well as R&D staff in industry.