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Incomplete Data And Data Dependencies In Relational Databases

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Incomplete Data And Data Dependencies In Relational Databases

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Author : Segio Greco
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2012-08-15

Incomplete Data And Data Dependencies In Relational Databases written by Segio Greco and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-15 with Computers categories.

The chase has long been used as a central tool to analyze dependencies and their effect on queries. It has been applied to different relevant problems in database theory such as query optimization, query containment and equivalence, dependency implication, and database schema design. Recent years have seen a renewed interest in the chase as an important tool in several database applications, such as data exchange and integration, query answering in incomplete data, and many others. It is well known that the chase algorithm might be non-terminating and thus, in order for it to find practical applicability, it is crucial to identify cases where its termination is guaranteed. Another important aspect to consider when dealing with the chase is that it can introduce null values into the database, thereby leading to incomplete data. Thus, in several scenarios where the chase is used the problem of dealing with data dependencies and incomplete data arises. This book discusses fundamental issues concerning data dependencies and incomplete data with a particular focus on the chase and its applications in different database areas. We report recent results about the crucial issue of identifying conditions that guarantee the chase termination. Different database applications where the chase is a central tool are discussed with particular attention devoted to query answering in the presence of data dependencies and database schema design. Table of Contents: Introduction / Relational Databases / Incomplete Databases / The Chase Algorithm / Chase Termination / Data Dependencies and Normal Forms / Universal Repairs / Chase and Database Applications

Incomplete Data And Data Dependencies In Relational Databases

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Author : Sergio Greco
language : en
Publisher: Springer Nature
Release Date : 2022-06-01

Incomplete Data And Data Dependencies In Relational Databases written by Sergio Greco and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.

Query Processing Over Incomplete Databases

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Author : Yunjun Gao
language : en
Publisher: Springer Nature
Release Date : 2022-06-01

Query Processing Over Incomplete Databases written by Yunjun Gao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.

Incomplete data is part of life and almost all areas of scientific studies. Users tend to skip certain fields when they fill out online forms; participants choose to ignore sensitive questions on surveys; sensors fail, resulting in the loss of certain readings; publicly viewable satellite map services have missing data in many mobile applications; and in privacy-preserving applications, the data is incomplete deliberately in order to preserve the sensitivity of some attribute values. Query processing is a fundamental problem in computer science, and is useful in a variety of applications. In this book, we mostly focus on the query processing over incomplete databases, which involves finding a set of qualified objects from a specified incomplete dataset in order to support a wide spectrum of real-life applications. We first elaborate the three general kinds of methods of handling incomplete data, including (i) discarding the data with missing values, (ii) imputation for the missing values, and (iii) just depending on the observed data values. For the third method type, we introduce the semantics of k-nearest neighbor (kNN) search, skyline query, and top-k dominating query on incomplete data, respectively. In terms of the three representative queries over incomplete data, we investigate some advanced techniques to process incomplete data queries, including indexing, pruning as well as crowdsourcing techniques.

The Problem Of Incomplete Information In Relational Databases

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Author : G. Grahne
language : en
Publisher: Springer Science & Business Media
Release Date : 1991-11-13

The Problem Of Incomplete Information In Relational Databases written by G. Grahne and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-11-13 with Computers categories.

Reviews of Environmental Contamination and Toxicology publishes authoritative reviews on the occurrence, effects, and fate of pesticide residues and other environmental contaminants. It will keep you informed of the latest significant issues by providing in-depth information in the areas of analytical chemistry, agricultural microbiology, biochemistry, human and veterinary medicine, toxicology, and food technology.

Foundations Of Data Quality Management

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Author : Wenfei Fan
language : en
Publisher: Springer Nature
Release Date : 2022-05-31

Foundations Of Data Quality Management written by Wenfei Fan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.

Data quality is one of the most important problems in data management. A database system typically aims to support the creation, maintenance, and use of large amount of data, focusing on the quantity of data. However, real-life data are often dirty: inconsistent, duplicated, inaccurate, incomplete, or stale. Dirty data in a database routinely generate misleading or biased analytical results and decisions, and lead to loss of revenues, credibility and customers. With this comes the need for data quality management. In contrast to traditional data management tasks, data quality management enables the detection and correction of errors in the data, syntactic or semantic, in order to improve the quality of the data and hence, add value to business processes. While data quality has been a longstanding problem for decades, the prevalent use of the Web has increased the risks, on an unprecedented scale, of creating and propagating dirty data. This monograph gives an overview of fundamental issues underlying central aspects of data quality, namely, data consistency, data deduplication, data accuracy, data currency, and information completeness. We promote a uniform logical framework for dealing with these issues, based on data quality rules. The text is organized into seven chapters, focusing on relational data. Chapter One introduces data quality issues. A conditional dependency theory is developed in Chapter Two, for capturing data inconsistencies. It is followed by practical techniques in Chapter 2b for discovering conditional dependencies, and for detecting inconsistencies and repairing data based on conditional dependencies. Matching dependencies are introduced in Chapter Three, as matching rules for data deduplication. A theory of relative information completeness is studied in Chapter Four, revising the classical Closed World Assumption and the Open World Assumption, to characterize incomplete information in the real world. A data currency model is presented in Chapter Five, to identify the current values of entities in a database and to answer queries with the current values, in the absence of reliable timestamps. Finally, interactions between these data quality issues are explored in Chapter Six. Important theoretical results and practical algorithms are covered, but formal proofs are omitted. The bibliographical notes contain pointers to papers in which the results were presented and proven, as well as references to materials for further reading. This text is intended for a seminar course at the graduate level. It is also to serve as a useful resource for researchers and practitioners who are interested in the study of data quality. The fundamental research on data quality draws on several areas, including mathematical logic, computational complexity and database theory. It has raised as many questions as it has answered, and is a rich source of questions and vitality. Table of Contents: Data Quality: An Overview / Conditional Dependencies / Cleaning Data with Conditional Dependencies / Data Deduplication / Information Completeness / Data Currency / Interactions between Data Quality Issues

Semantics Empowered Web 3 0

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Author : Amit Sheth
language : en
Publisher: Springer Nature
Release Date : 2022-05-31

Semantics Empowered Web 3 0 written by Amit Sheth and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.

After the traditional document-centric Web 1.0 and user-generated content focused Web 2.0, Web 3.0 has become a repository of an ever growing variety of Web resources that include data and services associated with enterprises, social networks, sensors, cloud, as well as mobile and other devices that constitute the Internet of Things. These pose unprecedented challenges in terms of heterogeneity (variety), scale (volume), and continuous changes (velocity), as well as present corresponding opportunities if they can be exploited. Just as semantics has played a critical role in dealing with data heterogeneity in the past to provide interoperability and integration, it is playing an even more critical role in dealing with the challenges and helping users and applications exploit all forms of Web 3.0 data. This book presents a unified approach to harness and exploit all forms of contemporary Web resources using the core principles of ability to associate meaning with data through conceptual or domain models and semantic descriptions including annotations, and through advanced semantic techniques for search, integration, and analysis. It discusses the use of Semantic Web standards and techniques when appropriate, but also advocates the use of lighter weight, easier to use, and more scalable options when they are more suitable. The authors' extensive experience spanning research and prototypes to development of operational applications and commercial technologies and products guide the treatment of the material. Table of Contents: Role of Semantics and Metadata / Types and Models of Semantics / Annotation -- Adding Semantics to Data / Semantics for Enterprise Data / Semantics for Services / Semantics for Sensor Data / Semantics for Social Data / Semantics for Cloud Computing / Semantics for Advanced Applications

Perspectives On Business Intelligence

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Author : Raymond T. Ng
language : en
Publisher: Springer Nature
Release Date : 2022-05-31

Perspectives On Business Intelligence written by Raymond T. Ng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.

In the 1980s, traditional Business Intelligence (BI) systems focused on the delivery of reports that describe the state of business activities in the past, such as for questions like "How did our sales perform during the last quarter?" A decade later, there was a shift to more interactive content that presented how the business was performing at the present time, answering questions like "How are we doing right now?" Today the focus of BI users are looking into the future. "Given what I did before and how I am currently doing this quarter, how will I do next quarter?" Furthermore, fuelled by the demands of Big Data, BI systems are going through a time of incredible change. Predictive analytics, high volume data, unstructured data, social data, mobile, consumable analytics, and data visualization are all examples of demands and capabilities that have become critical within just the past few years, and are growing at an unprecedented pace. This book introduces research problems and solutions on various aspects central to next-generation BI systems. It begins with a chapter on an industry perspective on how BI has evolved, and discusses how game-changing trends have drastically reshaped the landscape of BI. One of the game changers is the shift toward the consumerization of BI tools. As a result, for BI tools to be successfully used by business users (rather than IT departments), the tools need a business model, rather than a data model. One chapter of the book surveys four different types of business modeling. However, even with the existence of a business model for users to express queries, the data that can meet the needs are still captured within a data model. The next chapter on vivification addresses the problem of closing the gap, which is often significant, between the business and the data models. Moreover, Big Data forces BI systems to integrate and consolidate multiple, and often wildly different, data sources. One chapter gives an overview of several integration architectures for dealing with the challenges that need to be overcome. While the book so far focuses on the usual structured relational data, the remaining chapters turn to unstructured data, an ever-increasing and important component of Big Data. One chapter on information extraction describes methods for dealing with the extraction of relations from free text and the web. Finally, BI users need tools to visualize and interpret new and complex types of information in a way that is compelling, intuitive, but accurate. The last chapter gives an overview of information visualization for decision support and text.

Readings In Artificial Intelligence And Databases

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Author : John Mylopoulos
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-06-28

Readings In Artificial Intelligence And Databases written by John Mylopoulos and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Computers categories.

The interaction of database and AI technologies is crucial to such applications as data mining, active databases, and knowledge-based expert systems. This volume collects the primary readings on the interactions, actual and potential, between these two fields. The editors have chosen articles to balance significant early research and the best and most comprehensive articles from the 1980s. An in-depth introduction discusses basic research motivations, giving a survey of the history, concepts, and terminology of the interaction. Major themes, approaches and results, open issues and future directions are all discussed, including the results of a major survey conducted by the editors of current work in industry and research labs. Thirteen sections follow, each with a short introduction. Topics examined include semantic data models with emphasis on conceptual modeling techniques for databases and information systems and the integration of data model concepts in high-level data languages, definition and maintenance of integrity constraints in databases and knowledge bases, natural language front ends, object-oriented database management systems, implementation issues such as concurrency control and error recovery, and representation of time and knowledge incompleteness from the viewpoints of databases, logic programming, and AI.

Semantics In Databases

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Author : Bernhard Thalheim
language : en
Publisher: Springer Science & Business Media
Release Date : 1998-02-25

Semantics In Databases written by Bernhard Thalheim and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-02-25 with Computers categories.

This book presents a coherent suvey on exciting developments in database semantics. The origins of the volume date back to a workshop held in Prague, Czech Republic, in 1995. The nine revised full papers and surveys presented were carefully reviewed for inclusion in the book. They address more traditional aspects like dealing with integrity constraints and conceptual modeling as well as new areas of databases; object-orientation, incomplete information, database transformations and other issues are investigated by applying formal semantics, e.g. the evolving algebra semantics.

Community Search Over Big Graphs

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Author : Xin Huang
language : en
Publisher: Springer Nature
Release Date : 2022-05-31

Community Search Over Big Graphs written by Xin Huang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.

Communities serve as basic structural building blocks for understanding the organization of many real-world networks, including social, biological, collaboration, and communication networks. Recently, community search over graphs has attracted significantly increasing attention, from small, simple, and static graphs to big, evolving, attributed, and location-based graphs. In this book, we first review the basic concepts of networks, communities, and various kinds of dense subgraph models. We then survey the state of the art in community search techniques on various kinds of networks across different application areas. Specifically, we discuss cohesive community search, attributed community search, social circle discovery, and geo-social group search. We highlight the challenges posed by different community search problems. We present their motivations, principles, methodologies, algorithms, and applications, and provide a comprehensive comparison of the existing techniques. This book finally concludes by listing publicly available real-world datasets and useful tools for facilitating further research, and by offering further readings and future directions of research in this important and growing area.

Incomplete Data And Data Dependencies In Relational Databases

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