Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer support. This book introduces developments in automatic analysis and interpretation of process-operational data both in real-time and over the operational history, and describes new concepts and methodologies for developing intelligent, state space-based systems for process monitoring, control and diagnosis. The book brings together new methods and algorithms from process monitoring and control, data mining and knowledge discovery, artificial intelligence, pattern recognition, and causal relationship discovery, as well as signal processing. It also provides a framework for integrating plant operators and supervisors into the design of process monitoring and control systems.

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 Research and Advanced Technology for Digital Libaries, ECDL'99, held in Paris, France in September 1999. The 26 revised full papers presented were carefully reviewed and selected from a total of 124 submissions. The book is divided in topical sections on image categorization and access, audio and video in digital libraries, information retrieval, user adaptation, knowledge sharing, cross language issues, case studies, and modelling, accessability and connectedness.

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.

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.

The 1999 Workshop on Spatio-Temporal Database Management, held in Ed- burgh, Scotland, September 10 11, 1999, brought together leading researchers anddevelopersintheareaofspatio-temporaldatabasestodiscussthestate-- the-art in spatio-temporal research and applications and to understand the new challenges and future research directions in this emerging and rapidly advancing area. The workshop served as a forum for disseminating research and expe- ence in spatio-temporal databases and for maximizing interchange of knowledge among researchers from the established spatial and temporal database com- nities.Theexchangeofresearchideasandresultsnotonlycontributestothe academic arena, but also bene?ts the user and commercial communities. Theseproceedingscontainthe researchpapersselectedforpresentationatthe workshop. The workshop was conceived from the outset to have a general scope within its areaand to be internationalin participation.The callfor papers aimed to attract the highest quality and most up-to-date research contributions from around the world, and the workshop was co-located with VLDB 99, enabling many participants to conveniently attend both events and thereby facilitating the widest possible international participation. The call for papers attracted 30 research papers, which were submitted by authors from 14 countries and ?ve continents, clearly indicating the truly int- nationalnatureoftheemergingareaofspatio-temporaldatabases.Aprogram committee consisting of 25 researchers from four continents conducted four - viewsofeachpaperandselected13outstandingpapersofrpresentationand discussion at the workshop and inclusion in the proceedings. Spatio-temporal databases manage spatially and temporally referenced data. Thepapersincludedinthisvolumecoverdiverseaspectsofthemanagement ofsuchdata, andtheyhavebeenorganizedinto?vegroups: understanding andmanipulatingspatio-temporaldata;integration, exchange, andvisualization; query processing; index evaluation; and constraints and dependencies."

The need to electronically store, manipulate and analyze large-scale, high-dimensional data sets requires new computational methods. This book presents new intelligent data management methods and tools, including new results from the field of inference. Leading experts also map out future directions of intelligent data analysis. This book will be a valuable reference for researchers exploring the interdisciplinary area between statistics and computer science as well as for professionals applying advanced data analysis methods in industry.

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.

This book contains selected papers presented at the First NASA International Conference on Quantum Computing and Quantum Communications, QCQC'98, held in Palm Springs, California, USA in February 1998.As the record of the first large-scale meeting entirely devoted to quantum computing and communications, this book is a unique survey of the state-of-the-art in the area. The 43 carefully reviewed papers are organized in topical sections on entanglement and quantum algorithms, quantum cryptography, quantum copying and quantum information theory, quantum error correction and fault-tolerant quantum computing, and embodiments of quantum computers.

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.

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.

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.

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.

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.

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.

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).

This BriefBook is a much extended glossary or a much condensed handbook, depending on the way one looks at it. In encyclopedic format, it covers subjects in statistics, computing, analysis, and related fields, resulting in a book that is both an introduction and a reference for scientists and engineers, especially experimental physicists dealing with data analysis.

Environmental information systems (EIS) are concerned with the management of data about the soil, the water, the air, and the species in the world around us. This first textbook on the topic gives a conceptual framework for EIS by structuring the data flow into 4 phases: data capture, storage, analysis, and metadata management. This flow corresponds to a complex aggregation process gradually transforming the incoming raw data into concise documents suitable for high-level decision support. All relevant concepts are covered, including statistical classification, data fusion, uncertainty management, knowledge based systems, GIS, spatial databases, multidimensional access methods, object-oriented databases, simulation models, and Internet-based information management. Several case studies present EIS in practice.

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.

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.

Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.

This is the proceedings of the Fifth Conference of the International Federation of Classification Societies held in Kobe, Japan, on March 27-30, 1996: The astounding increase in computer usage over the past decade and the ever-increasing scope of global communication networks have ushered in the information age; however, human intelligence is required to make sense of this sea of data and to use it effectively. Consequently, the rapidly developing cross-disciplinary field of data science has come of age. This volume contains selected papers from the Fifth Conference of the International Federation of Classification Societies (IFCS-96), held in Kobe, Japan, in March 1996. A wide range of topics is covered, including theoretical and methodological advances relating to data gathering, classification and clustering, exploratory and multivariate data analysis, and knowledge seeking and discovery. A broad view of the state of the art is presented, making this an essential work not only for data analysts, mathematicians, and statisticians but also for researchers involved in data processing at all stages from data gathering to decision making.

The most important use of computing in the future will be in the context of the global "digital convergence" where everything becomes digital and every thing is inter-networked. The application will be dominated by storage, search, retrieval, analysis, exchange and updating of information in a wide variety of forms. Heavy demands will be placed on systems by many simultaneous re quests. And, fundamentally, all this shall be delivered at much higher levels of dependability, integrity and security. Increasingly, large parallel computing systems and networks are providing unique challenges to industry and academia in dependable computing, espe cially because of the higher failure rates intrinsic to these systems. The chal lenge in the last part of this decade is to build a systems that is both inexpensive and highly available. A machine cluster built of commodity hardware parts, with each node run ning an OS instance and a set of applications extended to be fault resilient can satisfy the new stringent high-availability requirements. The focus of this book is to present recent techniques and methods for im plementing fault-tolerant parallel and distributed computing systems. Section I, Fault-Tolerant Protocols, considers basic techniques for achieving fault-tolerance in communication protocols for distributed systems, including synchronous and asynchronous group communication, static total causal order ing protocols, and fail-aware datagram service that supports communications by time."

This book and sofwtare package provide a complement to the traditional data analysis tools already widely available. It presents an introduction to the analysis of data using neural networks. Neural network functions discussed include multilayer feed-forward networks using error back propagation, genetic algorithm-neural network hybrids, generalized regression neural networks, learning quantizer networks, and self-organizing feature maps. In an easy-to-use, Windows-based environment it offers a wide range of data analytic tools which are not usually found together: these include genetic algorithms, probabilistic networks, as well as a number of related techniques that support these - notably, fractal dimension analysis, coherence analysis, and mutual information analysis. The text presents a number of worked examples and case studies using Simulnet, the software package which comes with the book. Readers are assumed to have a basic understanding of computers and elementary mathematics. With this background, a reader will find themselves quickly conducting sophisticated hands-on analyses of data sets.