The Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2000) was held at the Keihanna-Plaza, Kyoto, Japan, April 18 - 20, 2000. PAKDD 2000 provided an international forum for researchers and applica tion developers to share their original research results and practical development experiences. A wide range of current KDD topics were covered including ma chine learning, databases, statistics, knowledge acquisition, data visualization, knowledge-based systems, soft computing, and high performance computing. It followed the success of PAKDD 97 in Singapore, PAKDD 98 in Austraha, and PAKDD 99 in China by bringing together participants from universities, indus try, and government from all over the world to exchange problems and challenges and to disseminate the recently developed KDD techniques. This PAKDD 2000 proceedings volume addresses both current issues and novel approaches in regards to theory, methodology, and real world application. The technical sessions were organized according to subtopics such as Data Mining Theory, Feature Selection and Transformation, Clustering, Application of Data Mining, Association Rules, Induction, Text Mining, Web and Graph Mining. Of the 116 worldwide submissions, 33 regular papers and 16 short papers were accepted for presentation at the conference and included in this volume. Each submission was critically reviewed by two to four program committee members based on their relevance, originality, quality, and clarity."

In the past decade visualization established its importance both in scientific research and in real-world applications. In this book 21 research papers and 9 case studies report on the latest results in volume and flow visualization and information visualization. Thus it is a valuable source of information not only for researchers but also for practitioners developing or using visualization applications.

These proceedings collect the papers selected for the 2nd International Conf- ence on Interoperating GeographicInformationSystems held in Zur .. ich, Switz- land, 10-12 March, 1999. Interoperabilityhasbecomeanissueinmanyareasofinformationtechnology in the last decade. Computers are used everywhere, and there is an increasing need to share various types of resources such as data and services. This is es- ciallytrueinthecontextofspatialinformation.Spatialdatahavebeencollected, digitized and stored in many di?erent and di?ering repositories. Computer so- ware has been developed to manage, analyse and visualize spatial information. Producing such data and software has become an important business oppor- nity. In everydayspatialinformation handling in manyorganisationsand o?ces, however, interoperability is far from being a matter of fact. Incompatibilities in data formats, software products, spatial conceptions, quality standards, and models of the world continue to create as synchronicity among constituent parts of operating spatial systems. As a follow-upto the ?rst InternationalConference on Interoperating Geographic Information Systems held 1997 in Santa Barbara, California, the Interop'99 tries to provide a scienti? c platform for researchers in this area. Theinternationalprogramcommitteecarefullyselected22papersforpres- tation at the conference and publication in this volume. Additionally, this v- ume contains three invited contributions by Gio Wiederhold, Adrian Cuthbert and Gun .. ther Landgraf. Every paper was sent to three members of the program committee and other experts for review. The reviews resulted in a three-day single-track conference program that left some room for a few half-day tutorials on various topics regarding GIS interoperability.

This volume contains the papers selected for presentation at the Third Paci?c- Asia Conference on Knowledge Discovery and Data Mining (PAKDD-99)held in the Xiangshan Hotel, Beijing, China, April 26-28, 1999. The conference was sp- sored by Tsinghua University, National Science Foundation of China, Chinese Computer Federation, Toshiba Corporation, and NEC Software Chugoku, Ltd. PAKDD-99 provided an international forum for the sharing of original research results and practical development experiences among researchers and application developers from di?erent KDD-related areas such as machine lea- ing, databases, statistics, knowledge acquisition, data visualization, knowled- based systems, soft computing, and high performance computing. It followed the success of PAKDD-97 held in Singapore in 1997 and PAKDD-98 held in A- tralia in 1998 by bringing together participants from universities, industry, and government. PAKDD-99 encouraged both new theory/methodologies and real world - plications, and covered broad and diverse topics in data mining and knowledge discovery. The technical sessions included: Association Rules Mining; Feature Selection and Generation; Mining in Semi, Un-structured Data; Interestingness, Surprisingness, and Exceptions; Rough Sets, Fuzzy Logic, and Neural Networks; Induction, Classi?cation, and Clustering; Causal Model and Graph-Based Me- ods; Visualization; Agent-Based, and Distributed Data Mining; Advanced Topics and New Methodologies. Of the 158 submissions, we accepted 29 regular papers and 37 short papers for presentation at the conference and for publication in this volume. In addition, over 20 papers were accepted for poster presentation.

The field of machine learning and data mining in connection with pattern recognition enjoys growing popularity and attracts many researchers. Automatic pattern recognition systems have proven successful in many applications. The wide use of these systems depends on their ability to adapt to changing environmental conditions and to deal with new objects. This requires learning capabilities on the parts of these systems. The exceptional attraction of learning in pattern recognition lies in the specific data themselves and the different stages at which they get processed in a pattern recognition system. This results a specific branch within the field of machine learning. At the workshop, were presented machine learning approaches for image pre-processing, image segmentation, recognition and interpretation. Machine learning systems were shown on applications such as document analysis and medical image analysis. Many databases are developed that contain multimedia sources such as images, measurement protocols, and text documents. Such systems should be able to retrieve these sources by content. That requires specific retrieval and indexing strategies for images and signals. Higher quality database contents can be achieved if it were possible to mine these databases for their underlying information. Such mining techniques have to consider the specific characteristic of the image sources. The field of mining multimedia databases is just starting out. We hope that our workshop can attract many other researchers to this subject.

Mobile Apps - Programme, die auf Smartphones ausgefuhrt werden - sind derzeit fast nur bei Konsumenten erfolgreich. Ein echtes App-Konzept fur den Business-Markt fehlt nach wie vor. Die Autoren zeigen in dem Band den Weg zu intelligenten Business-Apps fur mobile Geschaftsprozesse, mit deren Hilfe Kunden zeitnah und individuell informiert werden koennen. Die Autoren betrachten Fragen der Anwendung, der Technologie und des Marktes und berucksichtigen auch Cloud-Loesungen.

Database systems of the next generation are likely to be inherently very complex due to the diversity of requirements placed on them. Incorporating active, real time, and temporal virtues in one database system is an arduous effort but is also a commend able one. This book presents the proceedings of the Second International Workshop on Active, Real Time, and Temporal Database Systems (ARTDB 97), held in Como, Milan, in September 1997. The aim of the workshop was to bring researchers together from the active and real time research communities, and to examine the current state of the art in active, real time, and temporal database systems. This book offers a collection of papers presented at the ARTDB 97 workshop. The papers, many of them representing proficient and tenable results, illuminate the feasibility of building database system supporting reactive behavior, while enforcing timeliness and predictability. The book contains nine papers carefully reviewed and accepted by the program committee, three invited papers written by prominent researchers in the field, and two summaries of the panel discussions held at the workshop. The program committee received seventeen submissions, where each submission was reviewed by at least three program committee members. The two panel sessions focused on predictability issues and on practical experience of active, real time, and temporal database systems. The ARTDB 97 workshop was held in cooperation with the IEEE Technical Committees on Real Time Systems and Complexity in Computing, and the ACM Special Interest Group on Manipulation of Data.

The objective of the workshops associated with the ER'99 18th International Conference on Conceptual Modeling is to give participants access to high level presentations on specialized, hot, or emerging scientific topics. Three themes have been selected in this respect: - Evolution and Change in Data Management (ECDM'99) dealing with han dling the evolution of data and data structure, - Reverse Engineering in Information Systems (REIS'99) aimed at exploring the issues raised by legacy systems, - The World Wide Web and Conceptual Modehng (WWWCM'99) which ana lyzes the mutual contribution of WWW resources and techniques with con ceptual modeling. ER'99 has been organized so that there is no overlap between conference ses sions and the workshops. Therefore participants can follow both the conference and the workshop presentations they are interested in. I would like to thank the ER'99 program co-chairs, Jacky Akoka and Mokrane Bouzeghoub for having given me the opportunity to organize these workshops. I would also like to thank Stephen Liddle for his valuable help in managing the evaluation procedure for submitted papers and helping to prepare the workshop proceedings for publication. August 1999 Jacques Kouloumdjian Preface for ECDM'99 The first part of this volume contains the proceedings of the First International Workshop on Evolution and Change in Data Management, ECDM'99, which was held in conjunction with the 18th International Conference on Conceptual Modehng (ER'99) in Paris, France, November 15-18, 1999.

Information extraction (IE) is a new technology enabling relevant content to be extracted from textual information available electronically. IE essentially builds on natural language processing and computational linguistics, but it is also closely related to the well established area of information retrieval and involves learning. In concert with other promising intelligent information processing technologies like data mining, intelligent data analysis, text summarization, and information agents, IE plays a crucial role in dealing with the vast amounts of information accessible electronically, for example from the Internet. The book is based on the Second International School on Information Extraction, SCIE-99, held in Frascati near Rome, Italy in June/July 1999.

This book constitutes the refereed proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD'99, held in Prague, Czech Republic in September 1999.
The 28 revised full papers and 48 poster presentations were carefully reviewed and selected from 106 full papers submitted. The papers are organized in topical sections on time series, applications, taxonomies and partitions, logic methods, distributed and multirelational databases, text mining and feature selection, rules and induction, and interesting and unusual issues.

In the first part, this book analyzes the knowledge discovery process in order to understand the relations between knowledge discovery steps and focusing. The part devoted to the development of focusing solutions opens with an analysis of the state of the art, then introduces the relevant techniques, and finally culminates in implementing a unified approach as a generic sampling algorithm, which is then integrated into a commercial data mining system. The last part evaluates specific focusing solutions in various application domains. The book provides various appendicies enhancing easy accessibility.
The book presents a comprehensive introduction to focusing in the context of data mining and knowledge discovery. It is written for researchers and advanced students, as well as for professionals applying data mining and knowledge discovery techniques in practice.

The biennial International Conference on Case-Based Reasoning (ICCBR) - ries, which began in Sesimbra, Portugal, in 1995, was intended to provide an international forum for the best fundamental and applied research in case-based reasoning (CBR). It was hoped that such a forum would encourage the g- wth and rigor of the eld and overcome the previous tendency toward isolated national CBR communities. The foresight of the original ICCBR organizers has been rewarded by the growth of a vigorous and cosmopolitan CBR community. CBR is now widely recognized as a powerful and important computational technique for a wide range of practical applications. By promoting an exchange of ideas among CBR researchers from across the globe, the ICCBR series has facilitated the broader acceptance and use of CBR. ICCBR-99 has continued this tradition by attracting high-quality research and applications papers from around the world. Researchers from 21 countries submitted 80 papers to ICCBR-99. From these submissions, 17 papers were selected for long oral presentation, 7 were accepted for short oral presentation, and 19 papers were accepted as posters. This volume sets forth these 43 papers, which contain both mature work and innovative new ideas.

Formanyyearstheintersectionofcomputing anddataanalysiscontainedme- based statistics packages and not much else. Recently, statisticians have - braced computing, computer scientists have started using statistical theories and methods, and researchers in all corners have invented algorithms to nd structure in vast online datasets. Data analysts now have access to tools for exploratory data analysis, decision tree induction, causal induction, function - timation, constructingcustomizedreferencedistributions, andvisualization, and thereareintelligentassistantsto adviseonmatters ofdesignandanalysis.There aretoolsfortraditional, relativelysmallsamples, andalsoforenormousdatasets. In all, the scope for probing data in new and penetrating ways has never been so exciting. The IDA-99 conference brings together a wide variety of researchers c- cerned with extracting knowledge from data, including people from statistics, machine learning, neural networks, computer science, pattern recognition, da- base management, and other areas.The strategiesadopted by people from these areas are often di erent, and a synergy results if this is recognized. The IDA series of conferences is intended to stimulate interaction between these di erent areas, sothatmorepowerfultoolsemergeforextractingknowledgefromdataand a better understanding is developed of the process of intelligent data analysis. The result is a conference that has a clear focus (one application area: intelligent data analysis) and a broad scope (many di erent methods and techn

International Federation of Classification Societies The International Federation of Classification Societies (lFCS) is an agency for the dissemination of technical and scientific information concerning classification and multivariate data analysis in the broad sense and in as wide a range of applications as possible; founded in 1985 in Cambridge (UK) by the following Scientific Societies and Groups: - British Classification Society - BCS - Classification Society of North America - CSNA - Gesellschaft fUr Klassification - GfKI - Japanese Classification Society - JCS - Classification Group ofItalian Statistical Society - CGSIS - Societe Francophone de Classification - SFC Now the IFCS includes also the following Societies: - Dutch-Belgian Classification Society - VOC - Polish Classification Section - SKAD - Portuguese Classification Association - CLAD - Group at Large - Korean Classification Society - KCS IFCS-98, the Sixth Conference of the International Federation of Classification Societies, was held in Rome, from July 21 to 24, 1998. Five preceding conferences were held in Aachen (Germany), Charlottesville (USA), Edinburgh (UK), Paris (France), Kobe (Japan).

International Federation of Classification Societies The International Federation of Classification Societies (IFCS) is an agency for the dissemination of technical and scientific information concerning classification and data analysis in the broad sense and in as wide a* range of applications as possible; founded in 1985 in Cambridge (UK) from the following Scientific Societies and Groups: British Classification Society -BCS; Classification Society of North America -CSNA; Gesellschaft fUr Klassifikation -GfKl; Japanese Classification Society -JCS; Classification Group of Italian Statistical Society - COSIS; Societe Francophone de Classification -SFC. Now the IFCS includes the following Societies: Dutch-Belgian Classification Society - VOC; Polish Classification Section - SKAD; Portuguese Classification Association - CLAD; Group-at-Large; Korean Classification Society -KCS. Biannual Meeting of the Classification and Data Analysis Group of SIS The biannual meeting of the Classification and Data Analysis Group of Societa Italiana di Statistica (SIS) was held in Pescara, July 3 -4, 1997. The 69 papers presented were divided in 17 sessions. Each session was organized by a chairperson with two invited speakers and two contributed papers from a call for papers. All the works were referred. Furthermore, during the meeting a discussant was provided for each session. A short version of the papers (4 pages) was.published before the conference.

Die Schwelle zur Informationsgesellschaft ist nach 30 Jahren Diskussion schon uberschritten, auch wenn weltweit noch uber die Wege dorthin diskutiert wird. Aber anstatt Betrachtungen uber Diskussionszyklen erfordert die Unumkehrbarkeit der Informatisierung in allen Lebensbereichen die klare Analyse der gewachsenen Strukturen in Technik, OEkonomie, Recht und Gesellschaft, um darauf Zukunft konkret zu gestalten. Rund um den Begriff eines "informationellen Vertrauens, das in den letzten Jahrzehnten noch nicht entstanden ist, das aber notwendigerweise und dringend zur Informationsgesellschaft gehoert, beschreiben die Autoren aus Wissenschaft und Praxis aus allen Disziplinen die Ausgestaltung unserer bereits vernetzten Welt. Der Jahres-Reader versteht sich als eine Grundlage einer anstehenden Neuorientierung hin zu einer systematischen und abgestimmten Gestaltung der technischen, wirtschaftlichen und regulativen Organisation kunftiger Infrastrukturen.

This book constitutes the refereed proceedings of the Second Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD-98, held in Melbourne, Australia, in April 1998. The book presents 30 revised full papers selected from a total of 110 submissions; also included are 20 poster presentations. The papers contribute new results to all current aspects in knowledge discovery and data mining on the research level as well as on the level of systems development. Among the areas covered are machine learning, information systems, the Internet, statistics, knowledge acquisition, data visualization, software reengineering, and knowledge based systems.

For self-service data preparation, Tableau Prep is relatively easy to use-as long as you know how to clean and organize your datasets. Carl Allchin, from The Information Lab in London, gets you up to speed on Tableau Prep through a series of practical lessons that include methods for preparing, cleaning, automating, organizing, and outputting your datasets. Based on Allchin's popular blog, Preppin' Data, this practical guide takes you step-by-step through Tableau Prep's fundamentals. Self-service data preparation reduces the time it takes to complete data projects and improves the quality of your analyses. Discover how Tableau Prep helps you access your data and turn it into valuable information. Know what to look for when you prepare data Learn which Tableau Prep functions to use when working with data fields Analyze the shape and profile of your dataset Output data for analysis and learn how Tableau Prep automates your workflow Learn how to clean your dataset using Tableau Prep functions Explore ways to use Tableau Prep techniques in real-world scenarios Make your data available to others by managing and documenting the output

This final report on the Esprit project ORCHESTRA deals with the design and development of an advanced groupware environment. It provides a global perspective on the project from the technical, research and development, and marketing points of view.

"Tontechnik fur Mediengestalter" beschreibt nicht nur die Grundlagen von Audiotechniken, sondern vermittelt auch wichtiges Zusatzwissen fur die Gestaltung und Produktionsorganisation. Anschaulich und leicht verstandlich erlautert der Autor die Grundlagen und physikalischen Phanomene, wie Interferenzen oder Raumakustik. Er beschreibt die Arbeitsablaufe so, dass auch Auszubildende und Einsteiger im Produktionsalltag von Anfang an bestehen konnen. Mediengestalter arbeiten mit einer Vielzahl von Menschen zusammen, deren Befindlichkeiten sie berucksichtigen mussen. Deshalb sensibilisiert der Autor seine Leser auch fur das Umfeld einer Produktion."

Graph-based representation of images is becoming a popular tool since it represents in a compact way the structure of a scene to be analyzed and allows for an easy manipulation of sub-parts or of relationships between parts. Therefore, it is widely used to control the different levels from segmentation to interpretation. The 14 papers in this volume are grouped in the following subject areas: hypergraphs, recognition and detection, matching, segmentation, implementation problems, representation.

Database research in the last decade has increasingly focused on providing support for non-standard applications. One important domain is representation and processing of spatial information, needed, e.g., in geographical information systems. Spatial data types provide a fundamental abstraction for modeling the structure of geometric entities, their relationships, properties and operations. This monograph is an extensive survey of this field and introduces a new, general, sophisticated framework for the formal definition and robust implementation of spatial data types.

Before use, standard ERP systems such as SAP R/3 need to be customized to meet the concrete requirements of the individual enterprise. This book provides an overview of the process models, methods, and tools offered by SAP and its partners to support this complex and time-consuming process. It begins by characterizing the foundations of the latest ERP systems from both a conceptual and technical viewpoint, whereby the most important components and functions of SAP R/3 are described. The main part of the book then goes on to present the current methods and tools for the R/3 implementation based on newer process models (roadmaps).

Big Data in Radio Astronomy: Scientific Data Processing for Advanced Radio Telescopes provides the latest research developments in big data methods and techniques for radio astronomy. Providing examples from such projects as the Square Kilometer Array (SKA), the world's largest radio telescope that generates over an Exabyte of data every day, the book offers solutions for coping with the challenges and opportunities presented by the exponential growth of astronomical data. Presenting state-of-the-art results and research, this book is a timely reference for both practitioners and researchers working in radio astronomy, as well as students looking for a basic understanding of big data in astronomy.

Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems.