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Entity Resolution And Information Quality

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Entity Resolution and Information Quality

Entity Resolution and Information Quality Book
Author : John R. Talburt
Publisher : Elsevier
Release : 2011-01-14
ISBN : 9780123819734
Language : En, Es, Fr & De

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Book Description :

Entity Resolution and Information Quality presents topics and definitions, and clarifies confusing terminologies regarding entity resolution and information quality. It takes a very wide view of IQ, including its six-domain framework and the skills formed by the International Association for Information and Data Quality {IAIDQ). The book includes chapters that cover the principles of entity resolution and the principles of Information Quality, in addition to their concepts and terminology. It also discusses the Fellegi-Sunter theory of record linkage, the Stanford Entity Resolution Framework, and the Algebraic Model for Entity Resolution, which are the major theoretical models that support Entity Resolution. In relation to this, the book briefly discusses entity-based data integration (EBDI) and its model, which serve as an extension of the Algebraic Model for Entity Resolution. There is also an explanation of how the three commercial ER systems operate and a description of the non-commercial open-source system known as OYSTER. The book concludes by discussing trends in entity resolution research and practice. Students taking IT courses and IT professionals will find this book invaluable. First authoritative reference explaining entity resolution and how to use it effectively Provides practical system design advice to help you get a competitive advantage Includes a companion site with synthetic customer data for applicatory exercises, and access to a Java-based Entity Resolution program.

Entity Information Life Cycle for Big Data

Entity Information Life Cycle for Big Data Book
Author : John R. Talburt,Yinle Zhou
Publisher : Morgan Kaufmann
Release : 2015-04-20
ISBN : 012800665X
Language : En, Es, Fr & De

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Book Description :

Entity Information Life Cycle for Big Data walks you through the ins and outs of managing entity information so you can successfully achieve master data management (MDM) in the era of big data. This book explains big data’s impact on MDM and the critical role of entity information management system (EIMS) in successful MDM. Expert authors Dr. John R. Talburt and Dr. Yinle Zhou provide a thorough background in the principles of managing the entity information life cycle and provide practical tips and techniques for implementing an EIMS, strategies for exploiting distributed processing to handle big data for EIMS, and examples from real applications. Additional material on the theory of EIIM and methods for assessing and evaluating EIMS performance also make this book appropriate for use as a textbook in courses on entity and identity management, data management, customer relationship management (CRM), and related topics. Explains the business value and impact of entity information management system (EIMS) and directly addresses the problem of EIMS design and operation, a critical issue organizations face when implementing MDM systems Offers practical guidance to help you design and build an EIM system that will successfully handle big data Details how to measure and evaluate entity integrity in MDM systems and explains the principles and processes that comprise EIM Provides an understanding of features and functions an EIM system should have that will assist in evaluating commercial EIM systems Includes chapter review questions, exercises, tips, and free downloads of demonstrations that use the OYSTER open source EIM system Executable code (Java .jar files), control scripts, and synthetic input data illustrate various aspects of CSRUD life cycle such as identity capture, identity update, and assertions

Data Matching

Data Matching Book
Author : Peter Christen
Publisher : Springer Science & Business Media
Release : 2012-07-04
ISBN : 3642311644
Language : En, Es, Fr & De

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Book Description :

Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of data matching, and its scalability to large databases. Peter Christen’s book is divided into three parts: Part I, “Overview”, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, “Steps of the Data Matching Process”, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, “Further Topics”, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today. By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.

Effective Entity Resolution Methodology for Improving Data Quality and Reliability of Service oriented Applications

Effective Entity Resolution Methodology for Improving Data Quality and Reliability of Service oriented Applications Book
Author : Ewa Musial
Publisher : Unknown
Release : 2014
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Effective Entity Resolution Methodology for Improving Data Quality and Reliability of Service oriented Applications book written by Ewa Musial, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Information Quality and Governance for Business Intelligence

Information Quality and Governance for Business Intelligence Book
Author : Yeoh, William
Publisher : IGI Global
Release : 2013-12-31
ISBN : 1466648937
Language : En, Es, Fr & De

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Book Description :

Business intelligence initiatives have been dominating the technology priority list of many organizations. However, the lack of effective information quality and governance strategies and policies has been meeting these initiatives with some challenges. Information Quality and Governance for Business Intelligence presents the latest exchange of academic research on all aspects of practicing and managing information using a multidisciplinary approach that examines its quality for organizational growth. This book is an essential reference tool for researchers, practitioners, and university students specializing in business intelligence, information quality, and information systems.

Information Quality in Information Fusion and Decision Making

Information Quality in Information Fusion and Decision Making Book
Author : Éloi Bossé,Galina L. Rogova
Publisher : Springer
Release : 2019-04-02
ISBN : 303003643X
Language : En, Es, Fr & De

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Book Description :

This book presents a contemporary view of the role of information quality in information fusion and decision making, and provides a formal foundation and the implementation strategies required for dealing with insufficient information quality in building fusion systems for decision making. Information fusion is the process of gathering, processing, and combining large amounts of information from multiple and diverse sources, including physical sensors to human intelligence reports and social media. That data and information may be unreliable, of low fidelity, insufficient resolution, contradictory, fake and/or redundant. Sources may provide unverified reports obtained from other sources resulting in correlations and biases. The success of the fusion processing depends on how well knowledge produced by the processing chain represents reality, which in turn depends on how adequate data are, how good and adequate are the models used, and how accurate, appropriate or applicable prior and contextual knowledge is. By offering contributions by leading experts, this book provides an unparalleled understanding of the problem of information quality in information fusion and decision-making for researchers and professionals in the field.

Innovative Techniques and Applications of Entity Resolution

Innovative Techniques and Applications of Entity Resolution Book
Author : Wang, Hongzhi
Publisher : IGI Global
Release : 2014-02-28
ISBN : 1466651997
Language : En, Es, Fr & De

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Book Description :

Entity resolution is an essential tool in processing and analyzing data in order to draw precise conclusions from the information being presented. Further research in entity resolution is necessary to help promote information quality and improved data reporting in multidisciplinary fields requiring accurate data representation. Innovative Techniques and Applications of Entity Resolution draws upon interdisciplinary research on tools, techniques, and applications of entity resolution. This research work provides a detailed analysis of entity resolution applied to various types of data as well as appropriate techniques and applications and is appropriately designed for students, researchers, information professionals, and system developers.

Special Issue on Entity Resolution

Special Issue on Entity Resolution Book
Author : John R. Talburt
Publisher : Unknown
Release : 2013
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Special Issue on Entity Resolution book written by John R. Talburt, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Information Quality Management

Information Quality Management Book
Author : Latif Al-Hakim
Publisher : IGI Global
Release : 2007-01-01
ISBN : 1599040247
Language : En, Es, Fr & De

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Book Description :

Technologies such as the Internet and mobile commerce bring with them ubiquitous connectivity, real-time access, and overwhelming volumes of data and information. The growth of data warehouses and communication and information technologies has increased the need for high information quality management in organizations. Information Quality Management: Theory and Applications provides solutions to information quality problems becoming increasingly prevalent.Information Quality Management: Theory and Applications provides insights and support for professionals and researchers working in the field of information and knowledge management, information quality, practitioners and managers of manufacturing, and service industries concerned with the management of information.

Advances in Information and Communication

Advances in Information and Communication Book
Author : Kohei Arai,Rahul Bhatia
Publisher : Springer Nature
Release : 2020
ISBN : 3030731030
Language : En, Es, Fr & De

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Book Description :

This book aims to provide an international forum for scholarly researchers, practitioners and academic communities to explore the role of information and communication technologies and its applications in technical and scholarly development. The conference attracted a total of 464 submissions, of which 152 submissions (including 4 poster papers) have been selected after a double-blind review process. Academic pioneering researchers, scientists, industrial engineers and students will find this series useful to gain insight into the current research and next-generation information science and communication technologies. This book discusses the aspects of communication, data science, ambient intelligence, networking, computing, security and Internet of things, from classical to intelligent scope. The authors hope that readers find the volume interesting and valuable; it gathers chapters addressing tate-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of the future research.

High Quality Entity Resolution with Adaptive Similarity Functions

High Quality Entity Resolution with Adaptive Similarity Functions Book
Author : Rabia Turan
Publisher : Unknown
Release : 2011
ISBN : 9781124522081
Language : En, Es, Fr & De

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Book Description :

Real-world datasets often contain missing, erroneous, and duplicate data. If such problems with dataset are not corrected, the analysis results on it might lead to wrong decisions. Due to practical significance of the data quality problem, many creative techniques have been proposed in the past to address such problems. In this thesis, we address one such data cleaning challenge, called entity resolution that deals with ambiguous references in data and whose task is to identify all references that co-refer. In this thesis, we exploit additional information sources to improve the disambiguation quality and overcome the limitations of feature-based approaches. Implicit relationships between entities is one such information source. We exploit relationship analysis. The approach we utilize views data as an entity-relationship graph and rely on measuring the connection strength (CS) among various entities in the graph by using a connection strength model. We propose a new adaptive similarity function that improves the quality of these approaches by adaptively learning the CS measure using the available training data. Another information source is the web. We propose an approach that utilizes web querying to measure the correlation information between entities. We also develop a classifier that converts the web-based correlation statistics into ``co-refer'' or ``do-not-co-refer'' decisions. The classifier is based on skylines and leverages the fact that the classification results are utilized in clustering. Our extensive experiments show that the proposed techniques have significant improvement over the state-of-the-art approaches. Entity resolution solutions often produce results consisting of objects whose attributes may contain uncertainty. This uncertainty is frequently captured in the form of a set of multiple mutually exclusive value choices for each uncertain attribute along with a measure of probability for alternative values. However, the applications built on top of such data requires deterministic answers. Thus, we propose a linear time algorithm that finds a deterministic answer set, which maximizes the expected $F_\alpha$ measure of selection queries on top of such a probabilistic representation. The proposed solution gets near-optimal results.

Information Technology New Generations

Information Technology  New Generations Book
Author : Shahram Latifi
Publisher : Springer
Release : 2016-03-28
ISBN : 3319324675
Language : En, Es, Fr & De

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Book Description :

This book collects articles presented at the 13th International Conference on Information Technology- New Generations, April, 2016, in Las Vegas, NV USA. It includes over 100 chapters on critical areas of IT including Web Technology, Communications, Security, and Data Mining.

Entity Resolution for Large Scale Databases

Entity Resolution for Large Scale Databases Book
Author : Kunho Kim
Publisher : Unknown
Release : 2019
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Entity resolution involves the problem of identifying, matching, and grouping the same entities from a single collection or multiple ones of data. Real-world databases often comprise data from multiple sources; hence, this process is an essential preprocessing step for correctly processing queries on a particular entity. An example of entity resolution is finding a person's medical records from multiple hospital records. In entity resolution, there commonly arise two main problems. One is the issue of disambiguation (or deduplication), which involves clustering records that correspond to the same entity within a database. The other problem is record linkage which involves matching records between multiple databases. In this dissertation, we focus on studying entity resolution on large-scale structured data such as CiteSeerX, PubMed and the United States Patent and Trademark Office (USPTO) patent database in several aspects. First, we review our proposed entity resolution framework, and discuss how to apply the framework on two practical problems; inventor name disambiguation on the USPTO patent database and financial entity record linkage. Second, we investigate building a web service to improve ease of using entity resolution results in several scenarios. We define two types of queries--attribute and record-based ones--and discuss how we design the web service to handle those queries efficiently. We demonstrate that our algorithm can accelerate the record-based query by a factor of 4.01 compared to a baseline naive approach. Third, we discuss improving the entity resolution in two directions. One direction is to improve the blocking method to reduce unnecessary comparison to improve scalability on author name disambiguation problems. We show that our proposed conjuctive normal form (CNF) blocking tested on the entire PubMed database of 80 million author mentions efficiently removes 82.17% of all author record pairs. Another direction is to improve accuracy; we study enhancing pairwise classification, which estimates the probability of a pair of records being from the same name entity. Our purposed hybrid method using both structure-aware and global features shows an improvement on mean average precision by up to 7.45% points. Finally, we discuss entity and attribute extraction. Entity extraction is important in terms of improving the input data quality for entity resolution and can also be used to extract useful entities from external sources. In this dissertation, we study the problem of extracting entities for task oriented spoken language understanding in human-to-human conversation scenarios. Our proposed bidirectional LSTM architecture with supplemental knowledge extracted from web data, search engine query logs, prior sentences, and task transfer demnstrates an improvement in F1-score by up to 2.92% compared to existing approaches.

Foundations of Information and Knowledge Systems

Foundations of Information and Knowledge Systems Book
Author : Thomas Lukasiewicz,Attila Sali
Publisher : Springer
Release : 2012-02-29
ISBN : 3642284728
Language : En, Es, Fr & De

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Book Description :

This book constitutes the proceedings of the 7th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2012, held in Kiel, Germany, in March 2012. The 12 regular and 8 short papers, presented together with two invited talks in full paper-length, were carefully reviewed and selected from 53 submissions. The contributions cover foundational aspects of information and knowledge systems. These include the application of ideas, theories or methods from specific disciplines to information and knowledge systems, such as discrete mathematics, logic and algebra, model theory, informaiton theory, complexity theory, algorithmics and computation, statistics, and optimization.

Information Quality

Information Quality Book
Author : Ron S. Kenett,Galit Shmueli
Publisher : John Wiley & Sons
Release : 2016-10-13
ISBN : 1118890655
Language : En, Es, Fr & De

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Book Description :

Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools. Technology, however, fails to deliver insights with added value if the quality of the information it generates is not assured. Information Quality (InfoQ) is a tool developed by the authors to assess the potential of a dataset to achieve a goal of interest, using data analysis. Whether the information quality of a dataset is sufficient is of practical importance at many stages of the data analytics journey, from the pre-data collection stage to the post-data collection and post-analysis stages. It is also critical to various stakeholders: data collection agencies, analysts, data scientists, and management. This book: Explains how to integrate the notions of goal, data, analysis and utility that are the main building blocks of data analysis within any domain. Presents a framework for integrating domain knowledge with data analysis. Provides a combination of both methodological and practical aspects of data analysis. Discusses issues surrounding the implementation and integration of InfoQ in both academic programmes and business / industrial projects. Showcases numerous case studies in a variety of application areas such as education, healthcare, official statistics, risk management and marketing surveys. Presents a review of software tools from the InfoQ perspective along with example datasets on an accompanying website. This book will be beneficial for researchers in academia and in industry, analysts, consultants, and agencies that collect and analyse data as well as undergraduate and postgraduate courses involving data analysis.

Handbook of Research on Big Data Storage and Visualization Techniques

Handbook of Research on Big Data Storage and Visualization Techniques Book
Author : Segall, Richard S.,Cook, Jeffrey S.
Publisher : IGI Global
Release : 2018-01-05
ISBN : 1522531432
Language : En, Es, Fr & De

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Book Description :

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.

The Four Generations of Entity Resolution

The Four Generations of Entity Resolution Book
Author : George Papadakis,Ekaterini Ioannou,Emanouil Thanos
Publisher : Morgan & Claypool Publishers
Release : 2021-03-16
ISBN : 1636390579
Language : En, Es, Fr & De

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Book Description :

Information systems are part and parcel of organizations. Yet, organizations often struggle to realize the benefits that motivate their introduction of these systems. To derive benefit from a new information system, it must be integrated into the structures and processes of the organization. That is, the system must be organizationally implemented. This book is about organizational implementation, which requires thorough preparations but also continues long after the system has gone live: (1) During the preparations, the implementation is planned. This phase includes specifying the effects pursued with the system, adapting the system and organization to each other, and obtaining buy-in for the planned change. (2) At go-live, the system is put to operational use and the associated organizational changes take effect. This phase is about insisting on the planned change even though go-live is normally hectic and accompanied by a productivity dip. (3) During continued use after go-live, implementation continues as design in use. This phase is long and improvisational. It includes following up on effects realization, but it is just as much about embracing the opportunities that emerge from using the system. Apart from covering the three phases of organizational implementation, the book inserts implementation in an organizational-change context and discusses barriers to implementation as well as boosters of implementation. The book concludes with an outlook to larger-scale issues beyond the implementation of one system in one organization and with an overview of the competences needed in the implementation team, which runs the organizational implementation.

Measuring Data Quality for Ongoing Improvement

Measuring Data Quality for Ongoing Improvement Book
Author : Laura Sebastian-Coleman
Publisher : Newnes
Release : 2012-12-31
ISBN : 0123977541
Language : En, Es, Fr & De

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Book Description :

The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You’ll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be understood by both business and IT and provides practical guidance on how to apply the DQAF within any organization enabling you to prioritize measurements and effectively report on results. Strategies for using data measurement to govern and improve the quality of data and guidelines for applying the framework within a data asset are included. You’ll come away able to prioritize which measurement types to implement, knowing where to place them in a data flow and how frequently to measure. Common conceptual models for defining and storing of data quality results for purposes of trend analysis are also included as well as generic business requirements for ongoing measuring and monitoring including calculations and comparisons that make the measurements meaningful and help understand trends and detect anomalies. Demonstrates how to leverage a technology independent data quality measurement framework for your specific business priorities and data quality challenges Enables discussions between business and IT with a non-technical vocabulary for data quality measurement Describes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation

Improving Usability Safety and Patient Outcomes with Health Information Technology

Improving Usability  Safety and Patient Outcomes with Health Information Technology Book
Author : F. Lau,J.A. Bartle-Clar,G. Bliss
Publisher : IOS Press
Release : 2019-03-26
ISBN : 1614999511
Language : En, Es, Fr & De

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Book Description :

Information technology is revolutionizing healthcare, and the uptake of health information technologies is rising, but scientific research and industrial and governmental support will be needed if these technologies are to be implemented effectively to build capacity at regional, national and global levels. This book, "Improving Usability, Safety and Patient Outcomes with Health Information Technology", presents papers from the Information Technology and Communications in Health conference, ITCH 2019, held in Victoria, Canada from 14 to 17 February 2019. The conference takes a multi-perspective view of what is needed to move technology forward to sustained and widespread use by transitioning research findings and approaches into practice. Topics range from improvements in usability and training and the need for new and improved designs for information systems, user interfaces and interoperable solutions, to governmental policy, mandates, initiatives and the need for regulation. The knowledge and insights gained from the ITCH 2019 conference will surely stimulate fruitful discussions and collaboration to bridge research and practice and improve usability, safety and patient outcomes, and the book will be of interest to all those associated with the development, implementation and delivery of health IT solutions.

Analytic Methods in Systems and Software Testing

Analytic Methods in Systems and Software Testing Book
Author : Ron S. Kenett,Fabrizio Ruggeri,Frederick W. Faltin
Publisher : John Wiley & Sons
Release : 2018-09-04
ISBN : 1119271509
Language : En, Es, Fr & De

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Book Description :

A comprehensive treatment of systems and software testing using state of the art methods and tools This book provides valuable insights into state of the art software testing methods and explains, with examples, the statistical and analytic methods used in this field. Numerous examples are used to provide understanding in applying these methods to real-world problems. Leading authorities in applied statistics, computer science, and software engineering present state-of-the-art methods addressing challenges faced by practitioners and researchers involved in system and software testing. Methods include: machine learning, Bayesian methods, graphical models, experimental design, generalized regression, and reliability modeling. Analytic Methods in Systems and Software Testing presents its comprehensive collection of methods in four parts: Part I: Testing Concepts and Methods; Part II: Statistical Models; Part III: Testing Infrastructures; and Part IV: Testing Applications. It seeks to maintain a focus on analytic methods, while at the same time offering a contextual landscape of modern engineering, in order to introduce related statistical and probabilistic models used in this domain. This makes the book an incredibly useful tool, offering interesting insights on challenges in the field for researchers and practitioners alike. Compiles cutting-edge methods and examples of analytical approaches to systems and software testing from leading authorities in applied statistics, computer science, and software engineering Combines methods and examples focused on the analytic aspects of systems and software testing Covers logistic regression, machine learning, Bayesian methods, graphical models, experimental design, generalized regression, and reliability models Written by leading researchers and practitioners in the field, from diverse backgrounds including research, business, government, and consulting Stimulates research at the theoretical and practical level Analytic Methods in Systems and Software Testing is an excellent advanced reference directed toward industrial and academic readers whose work in systems and software development approaches or surpasses existing frontiers of testing and validation procedures. It will also be valuable to post-graduate students in computer science and mathematics.