Query Processing over Incomplete Databases PDF Download

Author: Yunjun Gao
Publisher: Springer Nature
ISBN: 303101863X
Category : Computers
Languages : en
Pages : 106

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Book Description
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.

Author: Mohammad Shamsul Arefin
Publisher: Springer Nature
ISBN: 981998937X
Category :
Languages : en
Pages : 1053

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Book Description

Author: Yahiko Kambayashi
Publisher: World Scientific
ISBN: 9814545031
Category :
Languages : en
Pages : 366

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Book Description
This volume is a progress report on the project Research and Development of Advanced Database Systems for Integration of Media and User Environments, supported by the Ministry of Education, Science, Sports and Culture of Japan. It investigates research on new database systems due to the recent development of network technology; a clearer picture of integration by database technology is drawn as a result.

Author: Masatoshi Yoshikawa
Publisher: World Scientific
ISBN: 9814545023
Category :
Languages : en
Pages : 338

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Book Description
With the rapid growth of computer and communication technologies, the creation, modification and distribution of digital multimedia information have become easier than ever. Such multimedia information includes still images, video, audio, texts and artifacts in virtual space. The efficient storage of valuable information and rapid access to it is crucial to all modern organizations.This proceedings volume consists of papers by researchers and academicians which explore the various aspects of the digital media information base. A special emphasis is placed on new database system technologies.

Author: Mohammad Shamsul Arefin
Publisher: Springer Nature
ISBN: 9811666369
Category : Technology & Engineering
Languages : en
Pages : 784

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Book Description
This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

Author: Amihai Motro
Publisher: Springer Science & Business Media
ISBN: 1461562457
Category : Computers
Languages : en
Pages : 473

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Book Description
As its title suggests, "Uncertainty Management in Information Systems" is a book about how information systems can be made to manage information permeated with uncertainty. This subject is at the intersection of two areas of knowledge: information systems is an area that concentrates on the design of practical systems that can store and retrieve information; uncertainty modeling is an area in artificial intelligence concerned with accurate representation of uncertain information and with inference and decision-making under conditions infused with uncertainty. New applications of information systems require stronger capabilities in the area of uncertainty management. Our hope is that lasting interaction between these two areas would facilitate a new generation of information systems that will be capable of servicing these applications. Although there are researchers in information systems who have addressed themselves to issues of uncertainty, as well as researchers in uncertainty modeling who have considered the pragmatic demands and constraints of information systems, to a large extent there has been only limited interaction between these two areas. As the subtitle, "From Needs to Solutions," indicates, this book presents view points of information systems experts on the needs that challenge the uncer tainty capabilities of present information systems, and it provides a forum to researchers in uncertainty modeling to describe models and systems that can address these needs.

Author: Hwanjo Yu
Publisher: Springer
ISBN: 364229023X
Category : Computers
Languages : en
Pages : 357

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Book Description
This book constitutes the workshop proceedings of the 17th International Conference on Database Systems for Advanced Applications, DASFAA 2012, held in Busan, South Korea, in April 2012. The volume contains five workshops, each focusing on specific area that contributes to the main themes of the DASFAA conference: The Second International Workshop on Flash-based Database Systems (FlashDB 2012), the First International Workshop on Information Technologies for Maritime and Logistics (ITEMS 2012), the Third International Workshop on Social Networks and Social Media Mining on the Web (SNSMW 2012), the Second International Workshop on Spatial Information Modeling, Management and Mining (SIM3 2012), and the Fifth International Workshop on Data Quality in Integration Systems (DQIS 2012).

Author: Sergio Greco
Publisher: Springer Nature
ISBN: 3031018931
Category : Computers
Languages : en
Pages : 111

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Book Description
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

Author: Jan Chomicki
Publisher: Springer Science & Business Media
ISBN: 1461556430
Category : Computers
Languages : en
Pages : 442

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

Author: Valentina Janev
Publisher: Springer Nature
ISBN: 3030531996
Category : Computers
Languages : en
Pages : 212

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Book Description
This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.