Web mining is moving the World Wide Web toward a more useful environment in which users can quickly and easily find the information they need. Web mining uses document content, hyperlink structure, and usage statistics to assist users in meeting their needed information. This book provides a record of current research and practical applications in Web searching. It includes techniques that will improve the utilization of the Web by the design of Websites, as well as the design and application of search agents. This book presents this research and related applications in a manner that encourages additional work toward improving the reduction of information overflow, which is so common today in Web search results.

Enterprises have made amazing advances by taking advantage of data about their business to provide predictions and understanding of their customers, markets, and products. But as the world of business becomes more interconnected and global, enterprise data is no long a monolith; it is just a part of a vast web of data. Managing data on a world-wide scale is a key capability for any business today. The Semantic Web treats data as a distributed resource on the scale of the World Wide Web, and incorporates features to address the challenges of massive data distribution as part of its basic design. The aim of the first two editions was to motivate the Semantic Web technology stack from end-to-end; to describe not only what the Semantic Web standards are and how they work, but also what their goals are and why they were designed as they are. It tells a coherent story from beginning to end of how the standards work to manage a world-wide distributed web of knowledge in a meaningful way. The third edition builds on this foundation to bring Semantic Web practice to enterprise. Fabien Gandon joins Dean Allemang and Jim Hendler, bringing with him years of experience in global linked data, to open up the story to a modern view of global linked data. While the overall story is the same, the examples have been brought up to date and applied in a modern setting, where enterprise and global data come together as a living, linked network of data. Also included with the third edition, all of the data sets and queries are available online for study and experimentation at data.world/swwo.

This book presents a foray into the fascinating process of risk management, beginning from classical methods and approaches to understanding risk all the way into cutting-age thinking. Risk management by necessity must lie at the heart of governing our ever more complex digital societies. New phenomena and activities necessitate a new look at how individuals, firms, and states manage the uncertainty they must operate in. Initial chapters provide an introduction to traditional methods and show how they can be built upon to better understand the workings of the modern economy. Later chapters review digital activities and assets like cryptocurrencies showing how such emergent risks can be conceptualized better. Network theory figures prominently and the book demonstrates how it can be used to gauge the risk in the digital sectors of the economy. Predicting the unpredictable black swan events is also discussed in view of a wider adoption of economic simulations. The journey concludes by looking at how individuals perceive risk and make decisions as they operate in a virtual social network. This book interests the academic audience, but it also features insights and novel research results that are relevant for practitioners and policymakers.

Climate and Environmental Database Systems contains the papers presented at the Second International Workshop on Climate and Environmental Database Systems, held November 21-23, 1995, in Hamburg, Germany. Climate and environmental data may be separated into two classes, large amounts of well structured data and smaller amounts of less structured data. The large amounts are produced by numerical climate models and by satellites, handling data in the order of magnitude of 100 Tbytes for the climate modelling sites and 1000 Tbytes for the recording and processing of satellite data. Smaller amounts of poorly structured data are the environmental data, which come mainly from observations and measurements. Present-day problems in data management are connected with a variety of data types. Climate and Environmental Database Systems addresses the state of the art, practical experience, and future perspectives for climate and environmental database systems, and may be used as a text for a graduate level course on the subject or as a reference for researchers or practitioners in industry.

How do preprocessing steps such as tokenization, stemming, and removing stop words affect predictive models? Build beginning-to-end workflows for predictive modeling using text as features Compare traditional machine learning methods and deep learning methods for text data

Written by leading industry experts, the Data Management Handbook is a comprehensive, single-volume guide to the most innovative ideas on ho w to plan, develop, and run a powerful data management function - as w ell as handle day-to-day operations. The book provides practical, hand s-on guidance on the strategic, tactical, and technical aspects of dat a management, offering an inside look at how leading companies in vari ous industries meet the challenges of moving to a data-sharing environ ment.

Topics covered include: The fundamentals of business process modeling, including workflow patterns, an in-depth treatment of process flexibility, including approaches to dealing with on-the-fly changes, unexpected exceptions, and constraint-based processes, Technological aspects of a modern BPM environment, including its architecture, process design environment, process engine, resource handler and other support services, a comparative insight into current approaches to business process modeling and execution such as BPMN, EPCs, BPEL, jBPM, OpenWFE, and Enhydra Shark, process mining, verification, integration and configuration; and case studies in health care and screen business.

This book provides a comprehensive treatment of the field of Business Process Management (BPM) with a focus on Business Process Automation. It achieves this by covering a wide range of topics, both introductory and advanced, illustrated through and grounded in the YAWL (Yet Another Workflow Language) language and corresponding open-source support environment. In doing so it provides the reader with a deep, timeless, and vendor-independent understanding of the essential ingredients of business process automation.

The BPM field is in a continual state of flux and is subject to both the ongoing proposal of new standards and the introduction of new tools and technology. Its fundamentals however are relatively stable and this book aims to equip the reader with both a thorough understanding of them and the ability to apply them to better understand, assess and utilize new developments in the BPM field.

As a consequence of its topic-based format and the inclusion of a broad range of exercises, the book is eminently suitable for use in tertiary education, both at the undergraduate and the postgraduate level, for students of computer science and information systems. BPM researchers and practitioners will also find it a valuable resource. The book serves as a unique reference to a varied and comprehensive collection of topics that are relevant to the business process life-cycle.

Soft Computing Applications for Database Technologies: Techniques and Issues treats the new, emerging discipline of soft computing, which exploits this data through tolerance for imprecision and uncertainty to achieve solutions for complex problems. Soft computing methodologies include fuzzy sets, neural networks, genetic algorithms, Bayesian belief networks and rough sets, which are explored in detail through case studies and in-depth research. The advent of soft computing marks a significant paradigm shift in computing, with a wide range of applications and techniques which are presented and discussed in the chapters of this book.

Most applications generate large datasets, like social networking and social influence programs, smart cities applications, smart house environments, Cloud applications, public web sites, scientific experiments and simulations, data warehouse, monitoring platforms, and e-government services. Data grows rapidly, since applications produce continuously increasing volumes of both unstructured and structured data. Large-scale interconnected systems aim to aggregate and efficiently exploit the power of widely distributed resources. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance and to create a smart environment. The impact on data processing, transfer and storage is the need to re-evaluate the approaches and solutions to better answer the user needs. A variety of solutions for specific applications and platforms exist so a thorough and systematic analysis of existing solutions for data science, data analytics, methods and algorithms used in Big Data processing and storage environments is significant in designing and implementing a smart environment. Fundamental issues pertaining to smart environments (smart cities, ambient assisted leaving, smart houses, green houses, cyber physical systems, etc.) are reviewed. Most of the current efforts still do not adequately address the heterogeneity of different distributed systems, the interoperability between them, and the systems resilience. This book will primarily encompass practical approaches that promote research in all aspects of data processing, data analytics, data processing in different type of systems: Cluster Computing, Grid Computing, Peer-to-Peer, Cloud/Edge/Fog Computing, all involving elements of heterogeneity, having a large variety of tools and software to manage them. The main role of resource management techniques in this domain is to create the suitable frameworks for development of applications and deployment in smart environments, with respect to high performance. The book focuses on topics covering algorithms, architectures, management models, high performance computing techniques and large-scale distributed systems.

This book intends to change the perception of modern day telecommunications. Communication systems, usually perceived as "dumb pipes", carrying information / data from one point to another, are evolved into intelligently communicating smart systems. The book introduces a new field of cloud communications. The concept, theory, and architecture of this new field of cloud communications are discussed. The book lays down nine design postulates that form the basis of the development of a first of its kind cloud communication paradigm entitled Green Symbiotic Cloud Communications or GSCC. The proposed design postulates are formulated in a generic way to form the backbone for development of systems and technologies of the future. The book can be used to develop courses that serve as an essential part of graduate curriculum in computer science and electrical engineering. Such courses can be independent or part of high-level research courses. The book will also be of interest to a wide range of readers including both scientific and non-scientific domains as it discusses innovations from a simplistic explanatory viewpoint.

The development of a methodology for using logic databases is essential if new users are to be able to use these systems effectively to solve their problems, and this remains a largely unrealized goal. A workshop was organized in conjunction with the ILPS '93 Conference in Vancouver in October 1993 to provide a forum for users and implementors of deductive systems to share their experience. The emphasis was on the use of deductive systems. In addition to paper presentations, a number of systems were demonstrated. The papers of this book were drawn largely from the papers presented at the workshop, which have been extended and revised for inclusion here, and also include some papers describing interesting applications that were not discussed at the workshop. The applications described here should be seen as a starting point: a number of promising application domains are identified, and several interesting application packages are described, which provide the inspiration for further development. Declarative rule-based database systems hold a lot of promise in a wide range of application domains, and we need a continued stream of application development to better understand this potential and how to use it effectively. This book contains the broadest collection to date of papers describing implemented, significant applications of logic databases, and database systems as well as potential database users in such areas as scientific data management and complex decision support.

Grid computing promises to transform the way organizations and individuals compute, communicate, and collaborate. Computational and Data Grids: Principles, Applications and Design offers critical perspectives on theoretical frameworks, methodologies, implementations, and cutting edge research in grid computing, bridging the gap between academia and the latest achievements of the computer industry. Useful for professionals and students involved or interested in the study, use, design, and development of grid computing, this book highlights both the basics of the field and in depth analyses of grid networks.

This book introduces the quantum mechanical framework to information retrieval scientists seeking a new perspective on foundational problems. As such, it concentrates on the main notions of the quantum mechanical framework and describes an innovative range of concepts and tools for modeling information representation and retrieval processes. The book is divided into four chapters. Chapter 1 illustrates the main modeling concepts for information retrieval (including Boolean logic, vector spaces, probabilistic models, and machine-learning based approaches), which will be examined further in subsequent chapters. Next, chapter 2 briefly explains the main concepts of the quantum mechanical framework, focusing on approaches linked to information retrieval such as interference, superposition and entanglement. Chapter 3 then reviews the research conducted at the intersection between information retrieval and the quantum mechanical framework. The chapter is subdivided into a number of topics, and each description ends with a section suggesting the most important reference resources. Lastly, chapter 4 offers suggestions for future research, briefly outlining the most essential and promising research directions to fully leverage the quantum mechanical framework for effective and efficient information retrieval systems. This book is especially intended for researchers working in information retrieval, database systems and machine learning who want to acquire a clear picture of the potential offered by the quantum mechanical framework in their own research area. Above all, the book offers clear guidance on whether, why and when to effectively use the mathematical formalism and the concepts of the quantum mechanical framework to address various foundational issues in information retrieval.

Advanced Signature Indexing for Multimedia and Web Applications presents the latest research developments in signature-based indexing and query processing, specifically in multimedia and Web domains. These domains now demand a different designation of hashing information in bit-strings (i.e., signatures), and new indexes and query processing methods. The book provides solutions to these issues and addresses the resulting requirements, which are not adequately handled by existing approaches. Examples of these applications include: searching for similar images, representing multi-theme layers in maps, recommending products to Web-clients, and indexing large Web-log files. Special emphasis is given to structure description, implementation techniques and clear evaluation of operations performed (from a performance perspective).

Advanced Signature Indexing for Multimedia and Web Applications is an excellent reference for professionals involved in the development of applications in multimedia databases or the Web and may also serve as a textbook for advanced level courses in database and information retrieval systems.

A timely survey of the field from the point of view of some of the subject's most active researchers. Divided into several parts organized by theme, the book first covers the underlying methodology regarding active rules, followed by formal specification, rule analysis, performance analysis, and support tools. It then moves on to the implementation of active rules in a number of commercial systems, before concluding with applications and future directions for research. All researchers in databases will find this a valuable overview of the topic.

Time is ubiquitous in information systems. Almost every enterprise faces the problem of its data becoming out of date. However, such data is often valu able, so it should be archived and some means to access it should be provided. Also, some data may be inherently historical, e.g., medical, cadastral, or ju dicial records. Temporal databases provide a uniform and systematic way of dealing with historical data. Many languages have been proposed for tem poral databases, among others temporal logic. Temporal logic combines ab stract, formal semantics with the amenability to efficient implementation. This chapter shows how temporal logic can be used in temporal database applica tions. Rather than presenting new results, we report on recent developments and survey the field in a systematic way using a unified formal framework [GHR94; Ch094]. The handbook [GHR94] is a comprehensive reference on mathematical foundations of temporal logic. In this chapter we study how temporal logic is used as a query and integrity constraint language. Consequently, model-theoretic notions, particularly for mula satisfaction, are of primary interest. Axiomatic systems and proof meth ods for temporal logic [GHR94] have found so far relatively few applications in the context of information systems. Moreover, one needs to bear in mind that for the standard linearly-ordered time domains temporal logic is not re cursively axiomatizable [GHR94]' so recursive axiomatizations are by necessity incomplete.

"Handbook of Open Source Tools" introduces a comprehensive collection of advanced open source tools useful in developing software applications. The book contains information on more than 200 open-source tools which include software construction utilities for compilers, virtual-machines, database, graphics, high-performance computing, OpenGL, geometry, algebra, graph theory, GUIs and more. Special highlights for software construction utilities and application libraries are included. Each tool is covered in the context of a real like application development setting. This unique handbook presents a comprehensive discussion of advanced tools, a valuable asset used by most application developers and programmers; includes a special focus on Mathematical Open Source Software not available in most Open Source Software books, and introduces several tools (eg ACL2, CLIPS, CUDA, and COIN) which are not known outside of select groups, but are very powerful.

"Handbook of Open Source Tools "is designed for application developers and programmers working with Open Source Tools. Advanced-level students concentrating on Engineering, Mathematics and Computer Science will find this reference a valuable asset as well.

CHARM '97 is the ninth in a series of working conferences devoted to the development and use of formal techniques in digital hardware design and verification. This series is held in collaboration with IFIP WG 10.5. Previous meetings were held in Europe every other year.

Requiring heterogeneous information systems to cooperate and communicate has now become crucial, especially in application areas like e-business, Web-based mash-ups and the life sciences. Such cooperating systems have to automatically and efficiently match, exchange, transform and integrate large data sets from different sources and of different structure in order to enable seamless data exchange and transformation.

The book edited by Bellahsene, Bonifati and Rahm provides an overview of the ways in which the schema and ontology matching and mapping tools have addressed the above requirements and points to the open technical challenges. The contributions from leading experts are structured into three parts: large-scale and knowledge-driven schema matching, quality-driven schema mapping and evolution, and evaluation and tuning of matching tasks. The authors describe the state of the art by discussing the latest achievements such as more effective methods for matching data, mapping transformation verification, adaptation to the context and size of the matching and mapping tasks, mapping-driven schema evolution and merging, and mapping evaluation and tuning. The overall result is a coherent, comprehensive picture of the field.

With this book, the editors introduce graduate students and advanced professionals to this exciting field. For researchers, they provide an up-to-date source of reference about schema and ontology matching, schema and ontology evolution, and schema merging.

This textbook integrates important mathematical foundations, efficient computational algorithms, applied statistical inference techniques, and cutting-edge machine learning approaches to address a wide range of crucial biomedical informatics, health analytics applications, and decision science challenges. Each concept in the book includes a rigorous symbolic formulation coupled with computational algorithms and complete end-to-end pipeline protocols implemented as functional R electronic markdown notebooks. These workflows support active learning and demonstrate comprehensive data manipulations, interactive visualizations, and sophisticated analytics. The content includes open problems, state-of-the-art scientific knowledge, ethical integration of heterogeneous scientific tools, and procedures for systematic validation and dissemination of reproducible research findings.Complementary to the enormous challenges related to handling, interrogating, and understanding massive amounts of complex structured and unstructured data, there are unique opportunities that come with access to a wealth of feature-rich, high-dimensional, and time-varying information. The topics covered in Data Science and Predictive Analytics address specific knowledge gaps, resolve educational barriers, and mitigate workforce information-readiness and data science deficiencies. Specifically, it provides a transdisciplinary curriculum integrating core mathematical principles, modern computational methods, advanced data science techniques, model-based machine learning, model-free artificial intelligence, and innovative biomedical applications. The book's fourteen chapters start with an introduction and progressively build foundational skills from visualization to linear modeling, dimensionality reduction, supervised classification, black-box machine learning techniques, qualitative learning methods, unsupervised clustering, model performance assessment, feature selection strategies, longitudinal data analytics, optimization, neural networks, and deep learning. The second edition of the book includes additional learning-based strategies utilizing generative adversarial networks, transfer learning, and synthetic data generation, as well as eight complementary electronic appendices. This textbook is suitable for formal didactic instructor-guided course education, as well as for individual or team-supported self-learning. The material is presented at the upper-division and graduate-level college courses and covers applied and interdisciplinary mathematics, contemporary learning-based data science techniques, computational algorithm development, optimization theory, statistical computing, and biomedical sciences. The analytical techniques and predictive scientific methods described in the book may be useful to a wide range of readers, formal and informal learners, college instructors, researchers, and engineers throughout the academy, industry, government, regulatory, funding, and policy agencies. The supporting book website provides many examples, datasets, functional scripts, complete electronic notebooks, extensive appendices, and additional materials.

The subject of error-control coding bridges several disciplines, in particular mathematics, electrical engineering and computer science. The theory of error-control codes is often described abstractly in mathematical terms only, for the benefit of other coding specialists. Such a theoretical approach to coding makes it difficult for engineers to understand the underlying concepts of error correction, the design of digital error-control systems, and the quantitative behavior of such systems. In this book only a minimal amount of mathematics is introduced in order to describe the many, sometimes mathematical, aspects of error-control coding. The concepts of error correction and detection are in many cases sufficiently straightforward to avoid highly theoretical algebraic constructions. The reader will find that the primary emphasis of the book is on practical matters, not on theoretical problems. In fact, much of the material covered is summarized by examples of real developments, and almost all of the error-correction and detection codes introduced are attached to related practical applications. Error-Control Coding for Data Networks takes a structured approach to channel-coding, starting with the basic coding concepts and working gradually towards the most sophisticated coding systems. The most popular applications are described throughout the book. These applications include the channel-coding techniques used in mobile communication systems, such as: the global system for mobile communications (GSM) and the code-division multiple-access (CDMA) system, coding schemes for High-Definition TeleVision (HDTV) system, the Compact Disk (CD), and Digital Video Disk (DVD), as well as theerror-control protocols for the data-link layers of networks, and much more. The book is compiled carefully to bring engineers, coding specialists, and students up to date in the important modern coding technologies. Both electrical engineering students and communication engineers will benefit from the information in this largely self-contained text on error-control system engineering.

This book surveys recent advances in Conversational Information Retrieval (CIR), focusing on neural approaches that have been developed in the last few years. Progress in deep learning has brought tremendous improvements in natural language processing (NLP) and conversational AI, leading to a plethora of commercial conversational services that allow naturally spoken and typed interaction, increasing the need for more human-centric interactions in IR. The book contains nine chapters. Chapter 1 motivates the research of CIR by reviewing the studies on how people search and subsequently defines a CIR system and a reference architecture which is described in detail in the rest of the book. Chapter 2 provides a detailed discussion of techniques for evaluating a CIR system – a goal-oriented conversational AI system with a human in the loop. Then Chapters 3 to 7 describe the algorithms and methods for developing the main CIR modules (or sub-systems). In Chapter 3, conversational document search is discussed, which can be viewed as a sub-system of the CIR system. Chapter 4 is about algorithms and methods for query-focused multi-document summarization. Chapter 5 describes various neural models for conversational machine comprehension, which generate a direct answer to a user query based on retrieved query-relevant documents, while Chapter 6 details neural approaches to conversational question answering over knowledge bases, which is fundamental to the knowledge base search module of a CIR system. Chapter 7 elaborates various techniques and models that aim to equip a CIR system with the capability of proactively leading a human-machine conversation. Chapter 8 reviews a variety of commercial systems for CIR and related tasks. It first presents an overview of research platforms and toolkits which enable scientists and practitioners to build conversational experiences, and continues with historical highlights and recent trends in a range of application areas. Chapter 9 eventually concludes the book with a brief discussion of research trends and areas for future work. The primary target audience of the book are the IR and NLP research communities. However, audiences with another background, such as machine learning or human-computer interaction, will also find it an accessible introduction to CIR.

This book collects ECM research from the academic discipline of Information Systems and related fields to support academics and practitioners who are interested in understanding the design, use and impact of ECM systems. It also provides a valuable resource for students and lecturers in the field.

Enterprise content management in Information Systems research Foundations, methods and cases consolidates our current knowledge on how today s organizations can manage their digital information assets. The business challenges related to organizational information management include reducing search times, maintaining information quality, and complying with reporting obligations and standards. Many of these challenges are well-known in information management, but because of the vast quantities of information being generated today, they are more difficult to deal with than ever. Many companies use the term enterprise content management (ECM) to refer to the management of all forms of information, especially unstructured information. While ECM systems promise to increase and maintain information quality, to streamline content-related business processes, and to track the lifecycle of information, their implementation poses several questions and challenges: Which content objects should be put under the control of the ECM system? Which processes are affected by the implementation? How should outdated technology be replaced? Research is challenged to support practitioners in answering these questions."

This book captures and communicates the wealth of architecture experience Capgemini has gathered as a member of The Open Group a " a vendor- and technology-neutral consortium formed by major industry players a " in developing, deploying, and using its a oeIntegrated Architecture Frameworka (IAF) since its origination in 1993. Today, many elements of IAF have been incorporated into the new version 9 of TOGAF, the related Open Group standard. The authors, all working on and with IAF for many years, here provide a full reference to IAF and a guide on how to apply it. In addition, they describe in detail the relations between IAF and the architecture standards TOGAF and Archimate and other development or process frameworks like ITIL, CMMI, and RUP. Their presentation is targeted at architects, project managers, and process analysts who have either considered or are already working with IAF a " they will find many roadmaps, case studies, checklists, and tips and advice for their daily work.

This book is a selection of results obtained within three years of research performed under SYNAT-a nation-wide scientific project aiming at creating an infrastructure for scientific content storage and sharing for academia, education and open knowledge society in Poland.

The book is intended to be the last of the series related to the SYNAT project. The previous books, titled "Intelligent Tools for Building a Scientific Information Platform" and "Intelligent Tools for Building a Scientific Information Platform: Advanced Architectures and Solutions," were published as volumes 390 and 467 in Springer's Studies in Computational Intelligence. Its contents is based on the SYNAT 2013 Workshop held in Warsaw. The papers included in this volume present an overview and insight into information retrieval, repository systems, text processing, ontology-based systems, text mining, multimedia data processing and advanced software engineering, addressing the problems of implementing intelligent tools for building a scientific information platform.