Author: Ning Zhong
Publisher: Springer
ISBN: 3540489126
Category : Computers
Languages : en
Pages : 566
Book Description
This book constitutes the refereed proceedings of the Third Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD '99, held in Beijing, China, in April 1999. The 29 revised full papers presented together with 37 short papers were carefully selected from a total of 158 submissions. The book is divided into sections on emerging KDD technology; association rules; feature selection and generation; mining in semi-unstructured data; interestingness, surprisingness, and exceptions; rough sets, fuzzy logic, and neural networks; induction, classification, and clustering; visualization; causal models and graph-based methods; agent-based and distributed data mining; and advanced topics and new methodologies.
Methodologies for Knowledge Discovery and Data Mining
Author: Ning Zhong
Publisher: Springer
ISBN: 3540489126
Category : Computers
Languages : en
Pages : 566
Book Description
This book constitutes the refereed proceedings of the Third Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD '99, held in Beijing, China, in April 1999. The 29 revised full papers presented together with 37 short papers were carefully selected from a total of 158 submissions. The book is divided into sections on emerging KDD technology; association rules; feature selection and generation; mining in semi-unstructured data; interestingness, surprisingness, and exceptions; rough sets, fuzzy logic, and neural networks; induction, classification, and clustering; visualization; causal models and graph-based methods; agent-based and distributed data mining; and advanced topics and new methodologies.
Publisher: Springer
ISBN: 3540489126
Category : Computers
Languages : en
Pages : 566
Book Description
This book constitutes the refereed proceedings of the Third Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD '99, held in Beijing, China, in April 1999. The 29 revised full papers presented together with 37 short papers were carefully selected from a total of 158 submissions. The book is divided into sections on emerging KDD technology; association rules; feature selection and generation; mining in semi-unstructured data; interestingness, surprisingness, and exceptions; rough sets, fuzzy logic, and neural networks; induction, classification, and clustering; visualization; causal models and graph-based methods; agent-based and distributed data mining; and advanced topics and new methodologies.
Logic Programming
Author: Jan Maluszynski
Publisher: MIT Press
ISBN: 9780262631808
Category : Computers
Languages : en
Pages : 454
Book Description
The themes of the 1997 conference are new theoretical and practical accomplishments in logic programming, new research directions where ideas originating from logic programming can play a fundamental role, and relations between logic programming and other fields of computer science. The annual International Logic Programming Symposium, traditionally held in North America, is one of the main international conferences sponsored by the Association of Logic Programming. The themes of the 1997 conference are new theoretical and practical accomplishments in logic programming, new research directions where ideas originating from logic programming can play a fundamental role, and relations between logic programming and other fields of computer science. Topics include theoretical foundations, constraints, concurrency and parallelism, deductive databases, language design and implementation, nonmonotonic reasoning, and logic programming and the Internet.
Publisher: MIT Press
ISBN: 9780262631808
Category : Computers
Languages : en
Pages : 454
Book Description
The themes of the 1997 conference are new theoretical and practical accomplishments in logic programming, new research directions where ideas originating from logic programming can play a fundamental role, and relations between logic programming and other fields of computer science. The annual International Logic Programming Symposium, traditionally held in North America, is one of the main international conferences sponsored by the Association of Logic Programming. The themes of the 1997 conference are new theoretical and practical accomplishments in logic programming, new research directions where ideas originating from logic programming can play a fundamental role, and relations between logic programming and other fields of computer science. Topics include theoretical foundations, constraints, concurrency and parallelism, deductive databases, language design and implementation, nonmonotonic reasoning, and logic programming and the Internet.
Knowledge Discovery and Measures of Interest
Author: Robert J. Hilderman
Publisher: Springer Science & Business Media
ISBN: 147573283X
Category : Computers
Languages : en
Pages : 170
Book Description
Knowledge Discovery and Measures of Interest is a reference book for knowledge discovery researchers, practitioners, and students. The knowledge discovery researcher will find that the material provides a theoretical foundation for measures of interest in data mining applications where diversity measures are used to rank summaries generated from databases. The knowledge discovery practitioner will find solid empirical evidence on which to base decisions regarding the choice of measures in data mining applications. The knowledge discovery student in a senior undergraduate or graduate course in databases and data mining will find the book is a good introduction to the concepts and techniques of measures of interest. In Knowledge Discovery and Measures of Interest, we study two closely related steps in any knowledge discovery system: the generation of discovered knowledge; and the interpretation and evaluation of discovered knowledge. In the generation step, we study data summarization, where a single dataset can be generalized in many different ways and to many different levels of granularity according to domain generalization graphs. In the interpretation and evaluation step, we study diversity measures as heuristics for ranking the interestingness of the summaries generated. The objective of this work is to introduce and evaluate a technique for ranking the interestingness of discovered patterns in data. It consists of four primary goals: To introduce domain generalization graphs for describing and guiding the generation of summaries from databases. To introduce and evaluate serial and parallel algorithms that traverse the domain generalization space described by the domain generalization graphs. To introduce and evaluate diversity measures as heuristic measures of interestingness for ranking summaries generated from databases. To develop the preliminary foundation for a theory of interestingness within the context of ranking summaries generated from databases. Knowledge Discovery and Measures of Interest is suitable as a secondary text in a graduate level course and as a reference for researchers and practitioners in industry.
Publisher: Springer Science & Business Media
ISBN: 147573283X
Category : Computers
Languages : en
Pages : 170
Book Description
Knowledge Discovery and Measures of Interest is a reference book for knowledge discovery researchers, practitioners, and students. The knowledge discovery researcher will find that the material provides a theoretical foundation for measures of interest in data mining applications where diversity measures are used to rank summaries generated from databases. The knowledge discovery practitioner will find solid empirical evidence on which to base decisions regarding the choice of measures in data mining applications. The knowledge discovery student in a senior undergraduate or graduate course in databases and data mining will find the book is a good introduction to the concepts and techniques of measures of interest. In Knowledge Discovery and Measures of Interest, we study two closely related steps in any knowledge discovery system: the generation of discovered knowledge; and the interpretation and evaluation of discovered knowledge. In the generation step, we study data summarization, where a single dataset can be generalized in many different ways and to many different levels of granularity according to domain generalization graphs. In the interpretation and evaluation step, we study diversity measures as heuristics for ranking the interestingness of the summaries generated. The objective of this work is to introduce and evaluate a technique for ranking the interestingness of discovered patterns in data. It consists of four primary goals: To introduce domain generalization graphs for describing and guiding the generation of summaries from databases. To introduce and evaluate serial and parallel algorithms that traverse the domain generalization space described by the domain generalization graphs. To introduce and evaluate diversity measures as heuristic measures of interestingness for ranking summaries generated from databases. To develop the preliminary foundation for a theory of interestingness within the context of ranking summaries generated from databases. Knowledge Discovery and Measures of Interest is suitable as a secondary text in a graduate level course and as a reference for researchers and practitioners in industry.
Author:
Publisher: IOS Press
ISBN:
Category :
Languages : en
Pages : 7289
Book Description
Publisher: IOS Press
ISBN:
Category :
Languages : en
Pages : 7289
Book Description
Pattern Recognition Algorithms for Data Mining
Author: Sankar K. Pal
Publisher: CRC Press
ISBN: 1135436401
Category : Computers
Languages : en
Pages : 275
Book Description
Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks. Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.
Publisher: CRC Press
ISBN: 1135436401
Category : Computers
Languages : en
Pages : 275
Book Description
Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks. Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.
Advances in Database Technology - EDBT 2000
Author: Carlo Zaniolo
Publisher: Springer Science & Business Media
ISBN: 3540672273
Category : Computers
Languages : en
Pages : 521
Book Description
EDBT 2000 is the seventh conference in a series dedicated to the advancement of database technology. This year’s conference special theme, \Connect Millions of Users and Data Sources," underscores the importance of databases for the information age that is dawning with the new millennium. The importance - rives not just from the observation that the information age essentially rests on theconvergenceofcommunications,computing,andstorage.Equallyimportant, many of the concepts and techniques underlying the success of databasesystems have independent meaning and impact for today’s distributed information s- tems. The papers in the volume should also be seen in this light. The EDBT 2000 conference program includes 30 research papers selected by the program committee out of 187 submissions, covering advances in research, development, and applications of databases. The conference program also - cludes six industry andapplications papers,a panel discussion,six tutorials,and several software demonstrations. The conference features three distinguished - vited speakers: Ashish Gupta discusses database issues in electronic commerce, Stefano Ceri addresses the impact and challenges of XML on databases, and Andreas Reuter shares his views on new perspectives on database technology. The technical contributions presented at the EDBT 2000 conference are colle- ed and preserved in this volume that we are pleased to present to you with the expectation that it will serve as a valuable research and reference tool in your professional life.
Publisher: Springer Science & Business Media
ISBN: 3540672273
Category : Computers
Languages : en
Pages : 521
Book Description
EDBT 2000 is the seventh conference in a series dedicated to the advancement of database technology. This year’s conference special theme, \Connect Millions of Users and Data Sources," underscores the importance of databases for the information age that is dawning with the new millennium. The importance - rives not just from the observation that the information age essentially rests on theconvergenceofcommunications,computing,andstorage.Equallyimportant, many of the concepts and techniques underlying the success of databasesystems have independent meaning and impact for today’s distributed information s- tems. The papers in the volume should also be seen in this light. The EDBT 2000 conference program includes 30 research papers selected by the program committee out of 187 submissions, covering advances in research, development, and applications of databases. The conference program also - cludes six industry andapplications papers,a panel discussion,six tutorials,and several software demonstrations. The conference features three distinguished - vited speakers: Ashish Gupta discusses database issues in electronic commerce, Stefano Ceri addresses the impact and challenges of XML on databases, and Andreas Reuter shares his views on new perspectives on database technology. The technical contributions presented at the EDBT 2000 conference are colle- ed and preserved in this volume that we are pleased to present to you with the expectation that it will serve as a valuable research and reference tool in your professional life.
Data Warehousing and Knowledge Discovery
Author: Mukesh Mohania
Publisher: Springer Science & Business Media
ISBN: 3540664580
Category : Business & Economics
Languages : en
Pages : 413
Book Description
This book constitutes the refereed proceedings of the First International Conference on Data Warehousing and Knowledge Discovery, DaWaK'99, held in Florence, Italy in August/September 1999. The 31 revised full papers and nine short papers presented were carefully reviewed and selected from 88 submissions. The book is divided in topical sections on data warehouse design; online analytical processing; view synthesis, selection, and optimization; multidimensional databases; knowledge discovery; association rules; inexing and object similarities; generalized association rules and data and web mining; time series data bases; data mining applications and data analysis.
Publisher: Springer Science & Business Media
ISBN: 3540664580
Category : Business & Economics
Languages : en
Pages : 413
Book Description
This book constitutes the refereed proceedings of the First International Conference on Data Warehousing and Knowledge Discovery, DaWaK'99, held in Florence, Italy in August/September 1999. The 31 revised full papers and nine short papers presented were carefully reviewed and selected from 88 submissions. The book is divided in topical sections on data warehouse design; online analytical processing; view synthesis, selection, and optimization; multidimensional databases; knowledge discovery; association rules; inexing and object similarities; generalized association rules and data and web mining; time series data bases; data mining applications and data analysis.
Intelligent Technologies for Information Analysis
Author: Ning Zhong
Publisher: Springer Science & Business Media
ISBN: 3662079526
Category : Computers
Languages : en
Pages : 724
Book Description
Intelligent Information Technology (iiT) encompasses the theories and ap plications of artificial intelligence, statistical pattern recognition, learning theory, data warehousing, data mining and knowledge discovery, Grid com puting, and autonomous agents and multi-agent systems in the context of today's as well as future IT, such as Electronic Commerce (EC), Business Intelligence (BI), Social Intelligence (SI), Web Intelligence (WI), Knowledge Grid (KG), and Knowledge Community (KC), among others. The multi-author monograph presents the current state of the research and development in intelligent technologies for information analysis, in par ticular, advances in agents, data mining, and learning theory, from both the oretical and application aspects. It investigates the future of information technology (IT) from a new intelligent IT (iiT) perspective, and highlights major iiT-related topics by structuring an introductory chapter and 22 sur vey/research chapters into 5 parts: (1) emerging data mining technology, (2) data mining for Web intelligence, (3) emerging agent technology, ( 4) emerging soft computing technology, and (5) statistical learning theory. Each chapter includes the original work of the author(s) as well as a comprehensive survey related to the chapter's topic. This book will become a valuable source of reference for R&D profession als active in advanced intelligent information technologies. Students as well as IT professionals and ambitious practitioners concerned with advanced in telligent information technologies will appreciate the book as a useful text enhanced by numerous illustrations and examples.
Publisher: Springer Science & Business Media
ISBN: 3662079526
Category : Computers
Languages : en
Pages : 724
Book Description
Intelligent Information Technology (iiT) encompasses the theories and ap plications of artificial intelligence, statistical pattern recognition, learning theory, data warehousing, data mining and knowledge discovery, Grid com puting, and autonomous agents and multi-agent systems in the context of today's as well as future IT, such as Electronic Commerce (EC), Business Intelligence (BI), Social Intelligence (SI), Web Intelligence (WI), Knowledge Grid (KG), and Knowledge Community (KC), among others. The multi-author monograph presents the current state of the research and development in intelligent technologies for information analysis, in par ticular, advances in agents, data mining, and learning theory, from both the oretical and application aspects. It investigates the future of information technology (IT) from a new intelligent IT (iiT) perspective, and highlights major iiT-related topics by structuring an introductory chapter and 22 sur vey/research chapters into 5 parts: (1) emerging data mining technology, (2) data mining for Web intelligence, (3) emerging agent technology, ( 4) emerging soft computing technology, and (5) statistical learning theory. Each chapter includes the original work of the author(s) as well as a comprehensive survey related to the chapter's topic. This book will become a valuable source of reference for R&D profession als active in advanced intelligent information technologies. Students as well as IT professionals and ambitious practitioners concerned with advanced in telligent information technologies will appreciate the book as a useful text enhanced by numerous illustrations and examples.
New Developments in Unsupervised Outlier Detection
Author: Xiaochun Wang
Publisher: Springer Nature
ISBN: 9811595194
Category : Technology & Engineering
Languages : en
Pages : 287
Book Description
This book enriches unsupervised outlier detection research by proposing several new distance-based and density-based outlier scores in a k-nearest neighbors’ setting. The respective chapters highlight the latest developments in k-nearest neighbor-based outlier detection research and cover such topics as our present understanding of unsupervised outlier detection in general; distance-based and density-based outlier detection in particular; and the applications of the latest findings to boundary point detection and novel object detection. The book also offers a new perspective on bridging the gap between k-nearest neighbor-based outlier detection and clustering-based outlier detection, laying the groundwork for future advances in unsupervised outlier detection research. The authors hope the algorithms and applications proposed here will serve as valuable resources for outlier detection researchers for years to come.
Publisher: Springer Nature
ISBN: 9811595194
Category : Technology & Engineering
Languages : en
Pages : 287
Book Description
This book enriches unsupervised outlier detection research by proposing several new distance-based and density-based outlier scores in a k-nearest neighbors’ setting. The respective chapters highlight the latest developments in k-nearest neighbor-based outlier detection research and cover such topics as our present understanding of unsupervised outlier detection in general; distance-based and density-based outlier detection in particular; and the applications of the latest findings to boundary point detection and novel object detection. The book also offers a new perspective on bridging the gap between k-nearest neighbor-based outlier detection and clustering-based outlier detection, laying the groundwork for future advances in unsupervised outlier detection research. The authors hope the algorithms and applications proposed here will serve as valuable resources for outlier detection researchers for years to come.
Advances in Data Mining
Author: Petra Perner
Publisher: Springer
ISBN: 3540461310
Category : Computers
Languages : en
Pages : 115
Book Description
This book presents papers describing selected projects on the topic of data mining in fields like e commerce, medicine, and knowledge management. The objective is to report on current results and at the same time to give a review on the present activities in this field in Germany. An effort has been made to include the latest scientific results, as well as lead the reader to the various fields of activity and the problems related to them. Knowledge discovery on the basis of web data is a wide and fast growing area. E commerce is the principal theme of motivation in this field, as companies invest large sums in the electronic market, in order to maximize their profits and minimize their risks. Other applications are telelearning, teleteaching, service support, and citizen information systems. Concerning these applications, there is a great need to understand and support the user by means of recommendation systems, adaptive information systems, as well as by personalization. In this respect Giudici and Blanc present in their paper procedures for the generation of associative models from the tracking behavior of the user. Perner and Fiss present in their paper a strategy for intelligent e marketing with web mining and personalization. Methods and procedures for the generation of associative rules are presented in the paper by Hipp, Güntzer, and Nakhaeidizadeh.
Publisher: Springer
ISBN: 3540461310
Category : Computers
Languages : en
Pages : 115
Book Description
This book presents papers describing selected projects on the topic of data mining in fields like e commerce, medicine, and knowledge management. The objective is to report on current results and at the same time to give a review on the present activities in this field in Germany. An effort has been made to include the latest scientific results, as well as lead the reader to the various fields of activity and the problems related to them. Knowledge discovery on the basis of web data is a wide and fast growing area. E commerce is the principal theme of motivation in this field, as companies invest large sums in the electronic market, in order to maximize their profits and minimize their risks. Other applications are telelearning, teleteaching, service support, and citizen information systems. Concerning these applications, there is a great need to understand and support the user by means of recommendation systems, adaptive information systems, as well as by personalization. In this respect Giudici and Blanc present in their paper procedures for the generation of associative models from the tracking behavior of the user. Perner and Fiss present in their paper a strategy for intelligent e marketing with web mining and personalization. Methods and procedures for the generation of associative rules are presented in the paper by Hipp, Güntzer, and Nakhaeidizadeh.