Clusters Orders And Trees Methods And Applications
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| Author | : Fuad Aleskerov |
| Publisher | : Springer |
| Total Pages | : 404 |
| Release | : 2014-06-11 |
| Genre | : Mathematics |
| ISBN | : 1493907425 |
The volume is dedicated to Boris Mirkin on the occasion of his 70th birthday. In addition to his startling PhD results in abstract automata theory, Mirkin’s ground breaking contributions in various fields of decision making and data analysis have marked the fourth quarter of the 20th century and beyond. Mirkin has done pioneering work in group choice, clustering, data mining and knowledge discovery aimed at finding and describing non-trivial or hidden structures—first of all, clusters, orderings and hierarchies—in multivariate and/or network data. This volume contains a collection of papers reflecting recent developments rooted in Mirkin’s fundamental contribution to the state-of-the-art in group choice, ordering, clustering, data mining and knowledge discovery. Researchers, students and software engineers will benefit from new knowledge discovery techniques and application directions.
| Author | : Poncelet, Pascal |
| Publisher | : IGI Global |
| Total Pages | : 324 |
| Release | : 2007-08-31 |
| Genre | : Computers |
| ISBN | : 1599041642 |
"This book provides an overall view of recent solutions for mining, and explores new patterns,offering theoretical frameworks and presenting challenges and possible solutions concerning pattern extractions, emphasizing research techniques and real-world applications. It portrays research applications in data models, methodologies for mining patterns, multi-relational and multidimensional pattern mining, fuzzy data mining, data streaming and incremental mining"--Provided by publisher.
| Author | : Christian Hennig |
| Publisher | : CRC Press |
| Total Pages | : 753 |
| Release | : 2015-12-16 |
| Genre | : Business & Economics |
| ISBN | : 1466551895 |
Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools.The
| Author | : George A. Vouros |
| Publisher | : Springer |
| Total Pages | : 561 |
| Release | : 2004-04-01 |
| Genre | : Computers |
| ISBN | : 3540246746 |
Arti?cial intelligence has attracted a renewed interest from distinguished sci- tists and has again raised new, more realistic this time, expectations for future advances regarding the development of theories, models and techniques and the use of them in applications pervading many areas of our daily life. The borders of human-level intelligence are still very far away and possibly unknown. Nev- theless, recent scienti?c work inspires us to work even harder in our exploration of the unknown lands of intelligence. This volume contains papers selected for presentation at the 3rd Hellenic Conference on Arti?cial Intelligence (SETN 2004), the o?cial meeting of the Hellenic Society for Arti?cial Intelligence (EETN). The ?rst meeting was held in the University of Piraeus, 1996 and the second in the Aristotle University of Thessaloniki (AUTH), 2002. SETN conferences play an important role in the dissemination of the in- vative and high-quality scienti?c results in arti?cial intelligence which are being produced mainly by Greek scientists in institutes all over the world. However, the most important e?ect of SETN conferences is that they provide the context in which people meet and get to know each other, as well as a very good opp- tunity for students to get closer to the results of innovative arti?cial intelligence research.
| Author | : Jérôme Euzenat |
| Publisher | : Springer |
| Total Pages | : 302 |
| Release | : 2006-09-14 |
| Genre | : Computers |
| ISBN | : 3540409319 |
This book constitutes the refereed proceedings of the 12th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2006. The 28 revised full papers presented together with the abstracts of 2 invited lectures were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on agents, constraints and optimization, user concerns, decision support, models and ontologies, machine learning, ontology manipulation, natural language processing, and applications.
| Author | : Jiawei Han |
| Publisher | : Elsevier |
| Total Pages | : 740 |
| Release | : 2011-06-09 |
| Genre | : Computers |
| ISBN | : 0123814804 |
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
| Author | : M. Teresa Anguera |
| Publisher | : Frontiers Media SA |
| Total Pages | : 418 |
| Release | : 2021-01-21 |
| Genre | : Science |
| ISBN | : 2889664163 |
| Author | : Lynne Billard |
| Publisher | : John Wiley & Sons |
| Total Pages | : 352 |
| Release | : 2019-08-12 |
| Genre | : Mathematics |
| ISBN | : 1119010381 |
Covers everything readers need to know about clustering methodology for symbolic data—including new methods and headings—while providing a focus on multi-valued list data, interval data and histogram data This book presents all of the latest developments in the field of clustering methodology for symbolic data—paying special attention to the classification methodology for multi-valued list, interval-valued and histogram-valued data methodology, along with numerous worked examples. The book also offers an expansive discussion of data management techniques showing how to manage the large complex dataset into more manageable datasets ready for analyses. Filled with examples, tables, figures, and case studies, Clustering Methodology for Symbolic Data begins by offering chapters on data management, distance measures, general clustering techniques, partitioning, divisive clustering, and agglomerative and pyramid clustering. Provides new classification methodologies for histogram valued data reaching across many fields in data science Demonstrates how to manage a large complex dataset into manageable datasets ready for analysis Features very large contemporary datasets such as multi-valued list data, interval-valued data, and histogram-valued data Considers classification models by dynamical clustering Features a supporting website hosting relevant data sets Clustering Methodology for Symbolic Data will appeal to practitioners of symbolic data analysis, such as statisticians and economists within the public sectors. It will also be of interest to postgraduate students of, and researchers within, web mining, text mining and bioengineering.
| Author | : Alan Bundy |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 156 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 3642603599 |
The purpose of "Artificial Intelligence Techniques: A Comprehensive Cata logue" is to promote interaction between members of the AI community. It does this by announcing the existence of AI techniques, and acting as a pointer into the literature. Thus the AI community has access to a common, extensional definition of the field, which promotes a common terminology, discourages the reinvention of wheels, and acts as a clearing house for ideas and algorithms. I am grateful to the impressive group of AI experts who have contributed the many descriptions of AI techniques which go to make up this Catalogue. They have managed to distill a very wide knowledge of AI into a very compact form. The Catalogue is a reference work providing a quick guide to the AI tech niques available for different tasks. Intentionally, it only provides a brief de scription of each technique, with no extended discussion of its historical origin or how it has been used in particular AI programs.
| Author | : Dinesh P. Mehta |
| Publisher | : Taylor & Francis |
| Total Pages | : 1120 |
| Release | : 2018-02-21 |
| Genre | : Computers |
| ISBN | : 1498701884 |
The Handbook of Data Structures and Applications was first published over a decade ago. This second edition aims to update the first by focusing on areas of research in data structures that have seen significant progress. While the discipline of data structures has not matured as rapidly as other areas of computer science, the book aims to update those areas that have seen advances. Retaining the seven-part structure of the first edition, the handbook begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next analyze miscellaneous data structures, which are well-known structures that elude easy classification. The book then addresses mechanisms and tools that were developed to facilitate the use of data structures in real programs. It concludes with an examination of the applications of data structures. Four new chapters have been added on Bloom Filters, Binary Decision Diagrams, Data Structures for Cheminformatics, and Data Structures for Big Data Stores, and updates have been made to other chapters that appeared in the first edition. The Handbook is invaluable for suggesting new ideas for research in data structures, and for revealing application contexts in which they can be deployed. Practitioners devising algorithms will gain insight into organizing data, allowing them to solve algorithmic problems more efficiently.
