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An Introduction To Duplicate Detection
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Book Synopsis An Introduction to Duplicate Detection by : Felix Nauman
Download or read book An Introduction to Duplicate Detection written by Felix Nauman and published by Springer Nature. This book was released on 2022-06-01 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the ever increasing volume of data, data quality problems abound. Multiple, yet different representations of the same real-world objects in data, duplicates, are one of the most intriguing data quality problems. The effects of such duplicates are detrimental; for instance, bank customers can obtain duplicate identities, inventory levels are monitored incorrectly, catalogs are mailed multiple times to the same household, etc. Automatically detecting duplicates is difficult: First, duplicate representations are usually not identical but slightly differ in their values. Second, in principle all pairs of records should be compared, which is infeasible for large volumes of data. This lecture examines closely the two main components to overcome these difficulties: (i) Similarity measures are used to automatically identify duplicates when comparing two records. Well-chosen similarity measures improve the effectiveness of duplicate detection. (ii) Algorithms are developed to perform on very large volumes of data in search for duplicates. Well-designed algorithms improve the efficiency of duplicate detection. Finally, we discuss methods to evaluate the success of duplicate detection. Table of Contents: Data Cleansing: Introduction and Motivation / Problem Definition / Similarity Functions / Duplicate Detection Algorithms / Evaluating Detection Success / Conclusion and Outlook / Bibliography
Book Synopsis An Introduction to Duplicate Detection by : Felix Naumann
Download or read book An Introduction to Duplicate Detection written by Felix Naumann and published by Morgan & Claypool Publishers. This book was released on 2010 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the ever increasing volume of data, data quality problems abound. Multiple, yet different representations of the same real-world objects in data, duplicates, are one of the most intriguing data quality problems. The effects of such duplicates are detrimental; for instance, bank customers can obtain duplicate identities, inventory levels are monitored incorrectly, catalogs are mailed multiple times to the same household, etc. Automatically detecting duplicates is difficult: First, duplicate representations are usually not identical but slightly differ in their values. Second, in principle all pairs of records should be compared, which is infeasible for large volumes of data. This lecture examines closely the two main components to overcome these difficulties: (i) Similarity measures are used to automatically identify duplicates when comparing two records. Well-chosen similarity measures improve the effectiveness of duplicate detection. (ii) Algorithms are developed to perform on very large volumes of data in search for duplicates. Well-designed algorithms improve the efficiency of duplicate detection. Finally, we discuss methods to evaluate the success of duplicate detection. Table of Contents: Data Cleansing: Introduction and Motivation / Problem Definition / Similarity Functions / Duplicate Detection Algorithms / Evaluating Detection Success / Conclusion and Outlook / Bibliography
Book Synopsis Detection Theory by : Neil A. Macmillan
Download or read book Detection Theory written by Neil A. Macmillan and published by Psychology Press. This book was released on 2004-09-22 with total page 599 pages. Available in PDF, EPUB and Kindle. Book excerpt: Detection Theory is an introduction to one of the most important tools for analysis of data where choices must be made and performance is not perfect. Originally developed for evaluation of electronic detection, detection theory was adopted by psychologists as a way to understand sensory decision making, then embraced by students of human memory. It has since been utilized in areas as diverse as animal behavior and X-ray diagnosis. This book covers the basic principles of detection theory, with separate initial chapters on measuring detection and evaluating decision criteria. Some other features include: *complete tools for application, including flowcharts, tables, pointers, and software; *student-friendly language; *complete coverage of content area, including both one-dimensional and multidimensional models; *separate, systematic coverage of sensitivity and response bias measurement; *integrated treatment of threshold and nonparametric approaches; *an organized, tutorial level introduction to multidimensional detection theory; *popular discrimination paradigms presented as applications of multidimensional detection theory; and *a new chapter on ideal observers and an updated chapter on adaptive threshold measurement. This up-to-date summary of signal detection theory is both a self-contained reference work for users and a readable text for graduate students and other researchers learning the material either in courses or on their own.
Book Synopsis Adaptive Windows for Duplicate Detection by : Uwe Draisbach
Download or read book Adaptive Windows for Duplicate Detection written by Uwe Draisbach and published by Universitätsverlag Potsdam. This book was released on 2012 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Duplicate detection is the task of identifying all groups of records within a data set that represent the same real-world entity, respectively. This task is difficult, because (i) representations might differ slightly, so some similarity measure must be defined to compare pairs of records and (ii) data sets might have a high volume making a pair-wise comparison of all records infeasible. To tackle the second problem, many algorithms have been suggested that partition the data set and compare all record pairs only within each partition. One well-known such approach is the Sorted Neighborhood Method (SNM), which sorts the data according to some key and then advances a window over the data comparing only records that appear within the same window. We propose several variations of SNM that have in common a varying window size and advancement. The general intuition of such adaptive windows is that there might be regions of high similarity suggesting a larger window size and regions of lower similarity suggesting a smaller window size. We propose and thoroughly evaluate several adaption strategies, some of which are provably better than the original SNM in terms of efficiency (same results with fewer comparisons).
Book Synopsis Introduction to Information Retrieval by : Christopher D. Manning
Download or read book Introduction to Information Retrieval written by Christopher D. Manning and published by Cambridge University Press. This book was released on 2008-07-07 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.
Download or read book Data Matching written by Peter Christen and published by Springer Science & Business Media. This book was released on 2012-07-04 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis An Introduction to Knowledge Graphs by : UMUTCAN. FENSEL SERLES (DIETER.)
Download or read book An Introduction to Knowledge Graphs written by UMUTCAN. FENSEL SERLES (DIETER.) and published by Springer Nature. This book was released on 2024 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook introduces the theoretical foundations of technologies essential for knowledge graphs. It also covers practical examples, applications and tools. Knowledge graphs are the most recent answer to the challenge of providing explicit knowledge about entities and their relationships by potentially integrating billions of facts from heterogeneous sources. The book is structured in four parts. For a start, Part I lays down the overall context of knowledge graph technology. Part II “Knowledge Representation” then provides a deep understanding of semantics as the technical core of knowledge graph technology. Semantics is covered from different perspectives, such as conceptual, epistemological and logical. Next, Part III “Knowledge Modelling” focuses on the building process of knowledge graphs. The book focuses on the phases of knowledge generation, knowledge hosting, knowledge assessment, knowledge cleaning, knowledge enrichment, and knowledge deployment to cover a complete life cycle for this process. Finally, Part IV (simply called “Applications”) presents various application areas in detail with concrete application examples as well as an outlook on additional trends that will emphasize the need for knowledge graphs even stronger. This textbook is intended for graduate courses covering knowledge graphs. Besides students in knowledge graph, Semantic Web, database, or information retrieval classes, also advanced software developers for Web applications or tools for Web data management will learn about the foundations and appropriate methods.
Book Synopsis Scalable Uncertainty Management by : Eyke Hüllermeier
Download or read book Scalable Uncertainty Management written by Eyke Hüllermeier and published by Springer. This book was released on 2012-09-11 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Scalable Uncertainty Management, SUM 2012, held in Marburg, Germany, in September 2012. The 41 revised full papers and 13 revised short papers were carefully reviewed and selected from 75 submissions. The papers cover topics in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information including applications in decision support systems, machine learning, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.
Book Synopsis Advances in Big Data and Cloud Computing by : J. Dinesh Peter
Download or read book Advances in Big Data and Cloud Computing written by J. Dinesh Peter and published by Springer. This book was released on 2018-12-12 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a compendium of the proceedings of the International Conference on Big Data and Cloud Computing. It includes recent advances in the areas of big data analytics, cloud computing, internet of nano things, cloud security, data analytics in the cloud, smart cities and grids, etc. This volume primarily focuses on the application of the knowledge that promotes ideas for solving the problems of the society through cutting-edge technologies. The articles featured in this proceeding provide novel ideas that contribute to the growth of world class research and development. The contents of this volume will be of interest to researchers and professionals alike.
Book Synopsis Data Deduplication Approaches by : Tin Thein Thwel
Download or read book Data Deduplication Approaches written by Tin Thein Thwel and published by Academic Press. This book was released on 2020-11-25 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the age of data science, the rapidly increasing amount of data is a major concern in numerous applications of computing operations and data storage. Duplicated data or redundant data is a main challenge in the field of data science research. Data Deduplication Approaches: Concepts, Strategies, and Challenges shows readers the various methods that can be used to eliminate multiple copies of the same files as well as duplicated segments or chunks of data within the associated files. Due to ever-increasing data duplication, its deduplication has become an especially useful field of research for storage environments, in particular persistent data storage. Data Deduplication Approaches provides readers with an overview of the concepts and background of data deduplication approaches, then proceeds to demonstrate in technical detail the strategies and challenges of real-time implementations of handling big data, data science, data backup, and recovery. The book also includes future research directions, case studies, and real-world applications of data deduplication, focusing on reduced storage, backup, recovery, and reliability. - Includes data deduplication methods for a wide variety of applications - Includes concepts and implementation strategies that will help the reader to use the suggested methods - Provides a robust set of methods that will help readers to appropriately and judiciously use the suitable methods for their applications - Focuses on reduced storage, backup, recovery, and reliability, which are the most important aspects of implementing data deduplication approaches - Includes case studies
Book Synopsis From Security to Community Detection in Social Networking Platforms by : Panagiotis Karampelas
Download or read book From Security to Community Detection in Social Networking Platforms written by Panagiotis Karampelas and published by Springer. This book was released on 2019-04-09 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on novel and state-of-the-art scientific work in the area of detection and prediction techniques using information found generally in graphs and particularly in social networks. Community detection techniques are presented in diverse contexts and for different applications while prediction methods for structured and unstructured data are applied to a variety of fields such as financial systems, security forums, and social networks. The rest of the book focuses on graph-based techniques for data analysis such as graph clustering and edge sampling. The research presented in this volume was selected based on solid reviews from the IEEE/ACM International Conference on Advances in Social Networks, Analysis, and Mining (ASONAM '17). Chapters were then improved and extended substantially, and the final versions were rigorously reviewed and revised to meet the series standards. This book will appeal to practitioners, researchers and students in the field.
Book Synopsis Soft Computing in XML Data Management by : Zongmin Ma
Download or read book Soft Computing in XML Data Management written by Zongmin Ma and published by Springer Science & Business Media. This book was released on 2010-07-07 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers in a great depth the fast growing topic of techniques, tools and applications of soft computing in XML data management. It is shown how XML data management (like model, query, integration) can be covered with a soft computing focus. This book aims to provide a single account of current studies in soft computing approaches to XML data management. The objective of the book is to provide the state of the art information to researchers, practitioners, and graduate students of the Web intelligence, and at the same time serving the information technology professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.
Book Synopsis Extending the Boundaries of Design Science Theory and Practice by : Bengisu Tulu
Download or read book Extending the Boundaries of Design Science Theory and Practice written by Bengisu Tulu and published by Springer. This book was released on 2019-05-14 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 14th International Conference on Designing for a Digital and Globalized World, DESRIST 2019, held Worcester, MA, USA, June 2019. The 20 revised full papers included in the volume were carefully reviewed and selected from 54 submissions. They are organized in the following topical sections: Design Science Research Theory and Methodology; Design Science Research Applications in Healthcare; Design Science Research Applications in Data Science; and Design Science Research Applications in Emerging Topics.
Book Synopsis Digital Libraries and Multimedia Archives by : Giuseppe Serra
Download or read book Digital Libraries and Multimedia Archives written by Giuseppe Serra and published by Springer. This book was released on 2018-01-11 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 14th Italian Research Conference on Digital Libraries, IRCDL 2018, held in Udine, Italy, in January 2018. The 14 full papers and 11 short papers presented were carefully selected from 30 submissions. The papers are organized in topical sections on digital library architecture; multimedia content analysis; models and applications.
Book Synopsis Microsoft Power Platform Functional Consultant: PL-200 Exam Guide by : Julian Sharp
Download or read book Microsoft Power Platform Functional Consultant: PL-200 Exam Guide written by Julian Sharp and published by Packt Publishing Ltd. This book was released on 2020-12-04 with total page 623 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get up to speed with expert tips, techniques, and the latest insights to confidently take the PL-200 exam Key FeaturesLearn effectively with the help of self-assessment questions, mock tests, and detailed explanations in this up-to-date study guideAddress the challenges faced by a functional consultant in day-to-day activitiesUnderstand how to configure, customize, and implement solutions based on Power PlatformBook Description The Power Platform Functional Consultant Associate (PL-200) exam tests and validates the practical skills of Power Platform users who are proficient in developing solutions by combining the tools in Power Platform and the Microsoft 365 ecosystem based on business needs. This certification guide offers complete, up-to-date coverage of the PL-200 exam so you can prepare effectively for the exam. Written in a clear, succinct way with self-assessment questions, exam tips, and mock exams with detailed explanations of solutions, this book covers common day-to-day activities involved in configuring Power Platform, such as managing entities, creating apps, implementing security, and managing system change. You'll also explore the role of a functional consultant in creating a data model in the Microsoft Dataverse (formerly Common Data Service). Moving ahead, you'll learn how to design the user experience and even build model-driven and canvas apps. As you progress, the book will show you how to manage automation and create chatbots. Finally, you'll understand how to display your data with Power BI and integrate Power Platform with Microsoft 365 and Microsoft Teams. By the end of this book, you'll be well-versed with the essential concepts and techniques required to prepare for the PL-200 certification exam. What you will learnUnderstand how to build apps that meet customer needsExtend the schema for Dataverse with entities, fields, and relationshipsCreate and configure automations to simplify user activitiesExplore various security features in Power Platform and learn how to implement themUse multiple data sources to create task- or role-based web and mobile applications for usersAutomate business processes and enhance the user experience with Power Automate and UI FlowsIntegrate various applications within the Microsoft ecosystem with Power PlatformWho this book is for This book is for functional consultants and business analysts who are involved in implementing solutions based on Power Platform or Dynamics 365. As the PL-200 exam is a pre-requisite for other role-based certifications in Power Platform and Microsoft Dynamics 365, individuals pursuing their careers in these domains will also find this book helpful. Basic knowledge of Power Platform and access to a Power Platform environment are required to get started with this book.
Book Synopsis Data Quality and Record Linkage Techniques by : Thomas N. Herzog
Download or read book Data Quality and Record Linkage Techniques written by Thomas N. Herzog and published by Springer Science & Business Media. This book was released on 2007-05-23 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a practical understanding of issues involved in improving data quality through editing, imputation, and record linkage. The first part of the book deals with methods and models, focusing on the Fellegi-Holt edit-imputation model, the Little-Rubin multiple-imputation scheme, and the Fellegi-Sunter record linkage model. The second part presents case studies in which these techniques are applied in a variety of areas, including mortgage guarantee insurance, medical, biomedical, highway safety, and social insurance as well as the construction of list frames and administrative lists. This book offers a mixture of practical advice, mathematical rigor, management insight and philosophy.
Book Synopsis Forensic Analytics by : Mark J. Nigrini
Download or read book Forensic Analytics written by Mark J. Nigrini and published by John Wiley & Sons. This book was released on 2020-04-20 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Become the forensic analytics expert in your organization using effective and efficient data analysis tests to find anomalies, biases, and potential fraud—the updated new edition Forensic Analytics reviews the methods and techniques that forensic accountants can use to detect intentional and unintentional errors, fraud, and biases. This updated second edition shows accountants and auditors how analyzing their corporate or public sector data can highlight transactions, balances, or subsets of transactions or balances in need of attention. These tests are made up of a set of initial high-level overview tests followed by a series of more focused tests. These focused tests use a variety of quantitative methods including Benford’s Law, outlier detection, the detection of duplicates, a comparison to benchmarks, time-series methods, risk-scoring, and sometimes simply statistical logic. The tests in the new edition include the newly developed vector variation score that quantifies the change in an array of data from one period to the next. The goals of the tests are to either produce a small sample of suspicious transactions, a small set of transaction groups, or a risk score related to individual transactions or a group of items. The new edition includes over two hundred figures. Each chapter, where applicable, includes one or more cases showing how the tests under discussion could have detected the fraud or anomalies. The new edition also includes two chapters each describing multi-million-dollar fraud schemes and the insights that can be learned from those examples. These interesting real-world examples help to make the text accessible and understandable for accounting professionals and accounting students without rigorous backgrounds in mathematics and statistics. Emphasizing practical applications, the new edition shows how to use either Excel or Access to run these analytics tests. The book also has some coverage on using Minitab, IDEA, R, and Tableau to run forensic-focused tests. The use of SAS and Power BI rounds out the software coverage. The software screenshots use the latest versions of the software available at the time of writing. This authoritative book: Describes the use of statistically-based techniques including Benford’s Law, descriptive statistics, and the vector variation score to detect errors and anomalies Shows how to run most of the tests in Access and Excel, and other data analysis software packages for a small sample of the tests Applies the tests under review in each chapter to the same purchasing card data from a government entity Includes interesting cases studies throughout that are linked to the tests being reviewed. Includes two comprehensive case studies where data analytics could have detected the frauds before they reached multi-million-dollar levels Includes a continually-updated companion website with the data sets used in the chapters, the queries used in the chapters, extra coverage of some topics or cases, end of chapter questions, and end of chapter cases. Written by a prominent educator and researcher in forensic accounting and auditing, the new edition of Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations is an essential resource for forensic accountants, auditors, comptrollers, fraud investigators, and graduate students.
