Uncertainty Handling and Quality Assessment in Data Mining provides an introduction to the application of these concepts in Knowledge Discovery and Data Mining. It reviews the state-of-the-art in uncertainty handling and discusses a framework for unveiling and handling uncertainty. Coverage of quality assessment begins with an introduction to cluster analysis and a comparison of the methods and approaches that may be used. The techniques and algorithms involved in other essential data mining tasks, such as classification and extraction of association rules, are also discussed together with a review of the quality criteria and techniques for evaluating the data mining results. This book presents a general framework for assessing quality and handling uncertainty which is based on tested concepts and theories. This framework forms the basis of an implementation tool, 'Uminer' which is introduced to the reader for the first time. This tool supports the key data mining tasks while enhancing the traditional processes for handling uncertainty and assessing quality. Aimed at IT professionals involved with data mining and knowledge discovery, the work is supported with case studies from epidemiology and telecommunications that illustrate how the tool works in 'real world' data mining projects. The book would also be of interest to final year undergraduates or post-graduate students looking at: databases, algorithms, artificial intelligence and information systems particularly with regard to uncertainty and quality assessment.

The first Annual Working Conference ofWG11.4oftheInter nationalFederationforInformation Processing (IFIP), focuseson variousstate of the art concepts in the field of Network and Dis tributedSystemsSecurity. Oursocietyisrapidly evolvingand irreversibly set onacourse governedby electronicinteractions. Wehave seen thebirthofe mail in the early seventies, and are now facing new challenging applicationssuchase commerce, e government, ....Themoreour societyrelies on electronicforms ofcommunication, themorethe securityofthesecommunicationnetworks isessentialforitswell functioning. Asaconsequence, researchonmethodsandtechniques toimprove network security iso fparam ount importance. ThisWorking Conference bringstogetherresearchersandprac tionersofvariousdisciplines, organisationsandcountries, todiscuss thelatestdevelopmentsinsecurity protocols, secure software engin eering, mobileagentsecurity, e commercesecurityandsecurityfor distributedcomputing. Wearealsopleasedtohaveattractedtwointernationalspeakers topresenttwo case studies, one dealing withBelgium'sintentionto replacetheidentity card ofitscitizensbyanelectronicversion, and theotherdiscussingtheimplicationsofthesecuritycertificationin amultinationalcorporation. ThisWorking Conference s houldalsobeconsideredasthekick off activity ofWG11.4, the aimsof which can be summarizedas follows: topromoteresearch on technical measures forsecuringcom puternetworks, including bothhardware andsoftware based techniques. to promote dissemination of research results in the field of network security in real lifenetworks in industry, academia and administrative ins titutions. viii topromoteeducationintheapplicationofsecuritytechniques, andtopromotegeneral awarenessa boutsecurityproblems in thebroadfieldofinformationtechnology. Researchers and practioners who want to get involved in this Working Group, are kindlyrequestedtocontactthechairman. MoreinformationontheworkingsofWG11.4isavailable from the officialIFIP website: http: //www.ifip.at.org/. Finally, wewish toexpressour gratitudetoallthosewho have contributedtothisconference in one wayoranother. Wearegr ate fultothe internationalrefereeboard whoreviewedallthe papers andtotheauthorsandinvitedspeakers, whosecontributionswere essential to the successof the conference. We would alsoliketo thanktheparticipantswhosepresenceand interest, togetherwith thechangingimperativesofsociety, willprovea drivingforce for futureconferen

This book provides an overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data. Over 170 figures are included in the book.

Combining knowledge with strategies, Data Structure Practice for Collegiate Programming Contests and Education presents the first comprehensive book on data structure in programming contests. This book is designed for training collegiate programming contest teams in the nuances of data structure and for helping college students in computer-related majors to gain deeper understanding of data structure. Based on successful experiences in many world-level contests, the book includes 204 typical problems and detailed analyses selected from the ACM International Collegiate Programming Contest and other major programming contests since 1990. It is divided into four sections that focus on: Fundamental programming skills Experiments for linear lists Experiments for trees Experiments for graphs Each chapter contains a set of problems and includes hints. The book also provides test data for most problems as well as sources and IDs for online judgments that help with improving programming skills. Introducing a multi-options model and considerations of context, Data Structure Practice for Collegiate Programming Contests and Education encourages students to think creatively in solving programming problems. By taking readers through practical contest problems from analysis to implementation, it provides a complete source for enhancing understanding and polishing skills in programming.

This book presents a new diagnostic information methodology to assess the quality of conversational telephone speech. For this, a conversation is separated into three individual conversational phases (listening, speaking, and interaction), and for each phase corresponding perceptual dimensions are identified. A new analytic test method allows gathering dimension ratings from non-expert test subjects in a direct way. The identification of the perceptual dimensions and the new test method are validated in two sophisticated conversational experiments. The dimension scores gathered with the new test method are used to determine the quality of each conversational phase, and the qualities of the three phases, in turn, are combined for overall conversational quality modeling. The conducted fundamental research forms the basis for the development of a preliminary new instrumental diagnostic conversational quality model. This multidimensional analysis of conversational telephone speech is a major landmark towards deeply analyzing conversational speech quality for diagnosis and optimization of telecommunication systems.

New state-of-the-art techniques for analyzing and managing Web data have emerged due to the need for dealing with huge amounts of data which are circulated on the Web. ""Web Data Management Practices: Emerging Techniques and Technologies"" provides a thorough understanding of major issues, current practices, and the main ideas in the field of Web data management, helping readers to identify current and emerging issues, as well as future trends in this area. ""Web Data Management Practices: Emerging Techniques and Technologies"" presents a complete overview of important aspects related to Web data management practices, such as: Web mining, Web data clustering, and others. This book also covers an extensive range of topics, including related issues about Web mining, Web caching and replication, Web services, and the XML standard.

This book investigates the powerful role of online intermediaries, which connect companies with their end customers, to facilitate joint product innovation. Especially in the healthcare context, such intermediaries deploy interactive online platforms to foster co-creation between engaged healthcare consumers and innovation-seeking healthcare companies. In three empirical studies, this book outlines the key characteristics of online intermediaries in healthcare, their distinct strategies, and the remaining challenges in the field. Readers will also be introduced to the stages companies go through in adopting such co-created solutions. As such, the work appeals for both its academic scope and practical reach.

The proliferation of digital computing devices and their use in communication has resulted in an increased demand for systems and algorithms capable of mining textual data. Thus, the development of techniques for mining unstructured, semi-structured, and fully-structured textual data has become increasingly important in both academia and industry.

This second volume continues to survey the evolving field of text mining - the application of techniques of machine learning, in conjunction with natural language processing, information extraction and algebraic/mathematical approaches, to computational information retrieval. Numerous diverse issues are addressed, ranging from the development of new learning approaches to novel document clustering algorithms, collectively spanning several major topic areas in text mining.

Features:

a [ Acts as an important benchmark in the development of current and future approaches to mining textual information

a [ Serves as an excellent companion text for courses in text and data mining, information retrieval and computational statistics

a [ Experts from academia and industry share their experiences in solving large-scale retrieval and classification problems

a [ Presents an overview of current methods and software for text mining

a [ Highlights open research questions in document categorization and clustering, and trend detection

a [ Describes new application problems in areas such as email surveillance and anomaly detection

Survey of Text Mining II offers a broad selection in state-of-the art algorithms and software for text mining from both academic and industrial perspectives, to generate interest and insight into the stateof the field. This book will be an indispensable resource for researchers, practitioners, and professionals involved in information retrieval, computational statistics, and data mining.

Michael W. Berry is a professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville.

Malu Castellanos is a senior researcher at Hewlett-Packard Laboratories in Palo Alto, California.

Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned.

Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases.

Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.

Web services and Service-Oriented Computing (SOC) have become thriving areas of academic research, joint university/industry research projects, and novel IT products on the market. SOC is the computing paradigm that uses Web services as building blocks for the engineering of composite, distributed applications out of the reusable application logic encapsulated by Web services. Web services could be considered the best-known and most standardized technology in use today for distributed computing over the Internet. This book is the second installment of a two-book collection covering the state-of-the-art of both theoretical and practical aspects of Web services and SOC research and deployments. Advanced Web Services specifically focuses on advanced topics of Web services and SOC and covers topics including Web services transactions, security and trust, Web service management, real-world case studies, and novel perspectives and future directions. The editors present foundational topics in the first book of the collection, Web Services Foundations (Springer, 2013). Together, both books comprise approximately 1400 pages and are the result of an enormous community effort that involved more than 100 authors, comprising the world's leading experts in this field.

This book provides the most complete formal specification of the semantics of the Business Process Model and Notation 2.0 standard (BPMN) available to date, in a style that is easily understandable for a wide range of readers - not only for experts in formal methods, but e.g. also for developers of modeling tools, software architects, or graduate students specializing in business process management. BPMN - issued by the Object Management Group - is a widely used standard for business process modeling. However, major drawbacks of BPMN include its limited support for organizational modeling, its only implicit expression of modalities, and its lack of integrated user interaction and data modeling. Further, in many cases the syntactical and, in particular, semantic definitions of BPMN are inaccurate, incomplete or inconsistent. The book addresses concrete issues concerning the execution semantics of business processes and provides a formal definition of BPMN process diagrams, which can serve as a sound basis for further extensions, i.e., in the form of horizontal refinements of the core language. To this end, the Abstract State Machine (ASMs) method is used to formalize the semantics of BPMN. ASMs have demonstrated their value in various domains, e.g. specifying the semantics of programming or modeling languages, verifying the specification of the Java Virtual Machine, or formalizing the ITIL change management process. This kind of improvement promotes more consistency in the interpretation of comprehensive models, as well as real exchangeability of models between different tools. In the outlook at the end of the book, the authors conclude with proposing extensions that address actor modeling (including an intuitive way to denote permissions and obligations), integration of user-centric views, a refined communication concept, and data integration.

With the ever increasing growth of services and the corresponding demand for Quality of Service requirements that are placed on IP-based networks, the essential aspects of network planning will be critical in the coming years. A wide number of problems must be faced in order for the next generation of IP networks to meet their expected performance. With Performance Evaluation and Planning Methods for the Next Generation Internet, the editors have prepared a volume that outlines and illustrates these developing trends.

A number of the problems examined and analyzed in the book are:

-The design of IP networks and guaranteed performance

-Performances of virtual private networks

-Network design and reliability

-The issues of pricing, routing and the management of QoS

-Design problems arising from wireless networks

-Controlling network congestion

-New applications spawned from Internet use

-Several new models are introduced that will lead to better Internet performance

These are a few of the problem areas addressed in the book and only a selective example of some of the coming key areas in networks requiring performance evaluation and network planning.

This book comprehensively introduces data deduplication technologies for storage systems. It first presents the overview of data deduplication including its theoretical basis, basic workflow, application scenarios and its key technologies, and then the book focuses on each key technology of the deduplication to provide an insight into the evolution of the technology over the years including chunking algorithms, indexing schemes, fragmentation reduced schemes, rewriting algorithm and security solution. In particular, the state-of-the-art solutions and the newly proposed solutions are both elaborated. At the end of the book, the author discusses the fundamental trade-offs in each of deduplication design choices and propose an open-source deduplication prototype. The book with its fundamental theories and complete survey can guide the beginners, students and practitioners working on data deduplication in storage system. It also provides a compact reference in the perspective of key data deduplication technologies for those researchers in developing high performance storage solutions.

Learn how applying risk management to each stage of the software engineering model can help the entire development process run on time and on budget. This practical guide identifies the potential threats associated with software development, explains how to establish an effective risk management program, and details the six critical steps involved in applying the process. It also explores the pros and cons of software and organizational maturity, discusses various software metrics approaches you can use to measure software quality, and highlights procedures for implementing a successful metrics program.

Ontological Engineering refers to the set of activities that concern the ontology development process, the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. During the last decade, increasing attention has been focused on ontologies and Ontological Engineering. Ontologies are now widely used in Knowledge Engineering, Artificial Intelligence and Computer Science; in applications related to knowledge management, natural language processing, e-commerce, intelligent integration information, information retrieval, integration of databases, b- informatics, and education; and in new emerging fields like the Semantic Web. Primary goals of this book are to acquaint students, researchers and developers of information systems with the basic concepts and major issues of Ontological Engineering, as well as to make ontologies more understandable to those computer science engineers that integrate ontologies into their information systems. We have paid special attention to the influence that ontologies have on the Semantic Web. Pointers to the Semantic Web appear in all the chapters, but specially in the chapter on ontology languages and tools.

The Turn analyzes the research of information seeking and retrieval (IS&R) and proposes a new direction of integrating research in these two areas: the fields should turn off their separate and narrow paths and construct a new avenue of research. An essential direction for this avenue is context as given in the subtitle Integration of Information Seeking and Retrieval in Context. Other essential themes in the book include:

IS&R research models, frameworks and theories; search and works tasks and situations in context; interaction between humans and machines; information acquisition, relevance and information use; research design and methodology based on a structured set of explicit variables - all set into the holistic cognitive approach. The present monograph invites the reader into a construction project - there is much research to do for a contextual understanding of IS&R.

The Turn represents a wide-ranging perspective of IS&R by providing a novel unique research framework, covering both individual and social aspects of information behavior, including the generation, searching, retrieval and use of information. Regarding traditional laboratory information retrieval research, the monograph proposes the extension of research toward actors, search and work tasks, IR interaction and utility of information. Regarding traditional information seeking research, it proposes the extension toward information access technology and work task contexts.

The Turn is the first synthesis of research in the broad area of IS&R ranging from systems oriented laboratory IR research to social science oriented information seeking studies.

The book introduces new techniques that imply rigorous lower bounds on the com plexity of some number-theoretic and cryptographic problems. It also establishes certain attractive pseudorandom properties of various cryptographic primitives. These methods and techniques are based on bounds of character sums and num bers of solutions of some polynomial equations over finite fields and residue rings. Other number theoretic techniques such as sieve methods and lattice reduction algorithms are used as well. The book also contains a number of open problems and proposals for further research. The emphasis is on obtaining unconditional rigorously proved statements. The bright side of this approach is that the results do not depend on any assumptions or conjectures. On the downside, the results are much weaker than those which are widely believed to be true. We obtain several lower bounds, exponential in terms of logp, on the degrees and orders of o polynomials; o algebraic functions; o Boolean functions; o linear recurrence sequences; coinciding with values of the discrete logarithm modulo a prime p at sufficiently many points (the number of points can be as small as pI/2+O: ). These functions are considered over the residue ring modulo p and over the residue ring modulo an arbitrary divisor d of p - 1. The case of d = 2 is of special interest since it corresponds to the representation of the rightmost bit of the discrete logarithm and defines whether the argument is a quadratic residue."

Logical Data Modeling offers business managers, analysts, and students a clear, basic systematic guide to defining business information structures in relational database terms. The approach, based on Clive Finkelstein s business-side Information Engineering, is hands-on, practical, and explicit in terminology and reasoning. Filled with illustrations, examples, and exercises, Logical Data Modeling makes its subject accessible to readers with only a limited knowledge of database systems. The book covers all essential topics thoroughly but succinctly: entities, associations, attributes, keys and inheritance, valid and invalid structures, and normalization. It also emphasizes communication with business and database specialists, documentation, and the use of Visible Systems' Visible Advantage enterprise modeling tool. The application of design patterns to logical data modeling provides practitioners with a practical tool for fast development. At the end, a chapter covers the issues that arise when the logical data model is translated into the design for a physical database."

Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection.

Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as application and evaluation of algorithms, and thus provide an excellent state-of-the-art overview.

The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas.

This book consists of an anthology of writings. The aim is to honour Marco to celebrate the 35th year of his academic career . The book consists of a collection of selected opinions in the field of IS. Some themes are: IT and Information Systems organizational impacts, Systems development, Business process management, Business organization, e-government, social impact of IT.

Over the last decade, a great amount of effort and resources have been invested in the development of Semantic Web Service (SWS) frameworks. Numerous description languages, frameworks, tools, and matchmaking and composition algorithms have been proposed. Nevertheless, when faced with a real-world problem, it is still very hard to decide which of these different approaches to use.

In this book, the editors present an overall overview and comparison of the main current evaluation initiatives for SWS. The presentation is divided into four parts, each referring to one of the evaluation initiatives. Part I covers the long-established first two tracks of the Semantic Service Selection (S3) Contest - the OWL-S matchmaker evaluation and the SAWSDL matchmaker evaluation. Part II introduces the new S3 Jena Geography Dataset (JGD) cross evaluation contest. Part III presents the Semantic Web Service Challenge. Lastly, Part IV reports on the semantic aspects of the Web Service Challenge. The introduction to each part provides an overview of the evaluation initiative and overall results for its latest evaluation workshops. The following chapters in each part, written by the participants, detail their approaches, solutions and lessons learned.This book is aimed at two different types of readers. Researchers on SWS technology receive an overview of existing approaches in SWS with a particular focus on evaluation approaches; potential users of SWS technologies receive a comprehensive summary of the respective strengths and weaknesses of current systems and thus guidance on factors that play a role in evaluation.

This book shows how business process management (BPM), as a management discipline at the intersection of IT and Business, can help organizations to master digital innovations and transformations. At the same time, it discusses how BPM needs to be further developed to successfully act as a driver for innovation in a digital world. In recent decades, BPM has proven extremely successful in managing both continuous and radical improvements in many sectors and business areas. While the digital age brings tremendous new opportunities, it also brings the specific challenge of correctly positioning and scoping BPM in organizations. This book shows how to leverage BPM to drive business innovation in the digital age. It brings together the views of the world's leading experts on BPM and also presents a number of practical cases. It addresses mangers as well as academics who share an interest in digital innovation and business process management. The book covers topics such as BPM and big data, BPM and the Internet of Things, and BPM and social media. While these technological and methodological aspects are key to BPM, process experts are also aware that further nontechnical organizational capabilities are required for successful innovation. The ideas presented in this book have helped us a lot while implementing process innovations in our global Logistics Service Center. Joachim Gantner, Director IT Services, Swarovski AG Managing Processes - everyone talks about it, very few really know how to make it work in today's agile and competitive world. It is good to see so many leading experts taking on the challenge in this book. Cornelius Clauser, Chief Process Officer, SAP SE This book provides worthwhile readings on new developments in advanced process analytics and process modelling including practical applications - food for thought how to succeed in the digital age. Ralf Diekmann, Head of Business Excellence, Hilti AG This book is as an important step towards process innovation systems. I very much like to congratulate the editors and authors for presenting such an impressive scope of ideas for how to address the challenging, but very rewarding marriage of BPM and innovation. Professor Michael Rosemann, Queensland University of Technology

This proceedings volume introduces recent work on the storage, retrieval and visualization of spatial Big Data, data-intensive geospatial computing and related data quality issues. Further, it addresses traditional topics such as multi-scale spatial data representations, knowledge discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data as more and more types of crowd sourcing spatial data are used in GIScience, such as movement trajectories, cellular phone calls, and social networks. In order to effectively manage these massive data collections, new methods and algorithms are called for. The book highlights state-of-the-art advances in the handling and application of spatial data, especially spatial Big Data, offering a cutting-edge reference guide for graduate students, researchers and practitioners in the field of GIScience.