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Query Processing over Incomplete Databases

Query Processing over Incomplete Databases PDF Author: Yunjun Gao
Publisher: Springer Nature
ISBN: 303101863X
Category : Computers
Languages : en
Pages : 106

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.

Query Processing over Incomplete Databases

Query Processing over Incomplete Databases PDF Author: Yunjun Gao
Publisher: Springer Nature
ISBN: 303101863X
Category : Computers
Languages : en
Pages : 106

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.

Advanced Machine Learning Technologies and Applications

Advanced Machine Learning Technologies and Applications PDF Author: Aboul-Ella Hassanien
Publisher: Springer Nature
ISBN: 3030697177
Category : Technology & Engineering
Languages : en
Pages : 1144

Book Description
This book presents the refereed proceedings of the 6th International Conference on Advanced Machine Learning Technologies and Applications (AMLTA 2021) held in Cairo, Egypt, during March 22–24, 2021, and organized by the Scientific Research Group of Egypt (SRGE). The papers cover current research Artificial Intelligence Against COVID-19, Internet of Things Healthcare Systems, Deep Learning Technology, Sentiment analysis, Cyber-Physical System, Health Informatics, Data Mining, Power and Control Systems, Business Intelligence, Social media, Control Design, and Smart Systems.

Query Processing over Uncertain Databases

Query Processing over Uncertain Databases PDF Author: Lei Chen
Publisher: Springer Nature
ISBN: 3031018966
Category : Computers
Languages : en
Pages : 91

Book Description
Due to measurement errors, transmission lost, or injected noise for privacy protection, uncertainty exists in the data of many real applications. However, query processing techniques for deterministic data cannot be directly applied to uncertain data because they do not have mechanisms to handle data uncertainty. Therefore, efficient and effective manipulation of uncertain data is a practical yet challenging research topic. In this book, we start from the data models for imprecise and uncertain data, move on to defining different semantics for queries on uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases. The book serves as a comprehensive guideline for query processing over uncertain databases. Table of Contents: Introduction / Uncertain Data Models / Spatial Query Semantics over Uncertain Data Models / Spatial Query Processing over Uncertain Databases / Conclusion

Data Streams

Data Streams PDF Author: S. Muthukrishnan
Publisher: Now Publishers Inc
ISBN: 193301914X
Category : Computers
Languages : en
Pages : 136

Book Description
In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time, and number of passes. Some of the methods rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity. The applications for this scenario include IP network traffic analysis, mining text message streams and processing massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges.

Relevant Query Answering over Streaming and Distributed Data

Relevant Query Answering over Streaming and Distributed Data PDF Author: Shima Zahmatkesh
Publisher: Springer Nature
ISBN: 3030383393
Category : Computers
Languages : en
Pages : 128

Book Description
This book examines the problem of relevant query answering over the Web and provides a comprehensive overview of relevant query answering over streaming and distributed data. In recent years, Web applications that combine highly dynamic data streams with data distributed over the Web to provide relevant answers have attracted increasing attention. Answering in a timely fashion, i.e., reactively, is one of the most important performance indicators, especially when the distributed data is evolving. The book proposes a solution that retains a local replica of the distributed data and offers various maintenance policies to refresh the replica over time. A limited refresh budget guarantees the reactiveness of the system. Focusing on stream processing and Semantic Web, it appeals to scientists and graduate students in the field.

Query Processing Over Live and Archived Data Streams

Query Processing Over Live and Archived Data Streams PDF Author: Sirish Chandrasekaran
Publisher:
ISBN:
Category :
Languages : en
Pages : 376

Book Description


Adaptive Query Processing

Adaptive Query Processing PDF Author: Amol Deshpande
Publisher: Now Publishers Inc
ISBN: 1601980345
Category : Computers
Languages : en
Pages : 156

Book Description
Adaptive Query Processing surveys the fundamental issues, techniques, costs, and benefits of adaptive query processing. It begins with a broad overview of the field, identifying the dimensions of adaptive techniques. It then looks at the spectrum of approaches available to adapt query execution at runtime - primarily in a non-streaming context. The emphasis is on simplifying and abstracting the key concepts of each technique, rather than reproducing the full details available in the papers. The authors identify the strengths and limitations of the different techniques, demonstrate when they are most useful, and suggest possible avenues of future research. Adaptive Query Processing serves as a valuable reference for students of databases, providing a thorough survey of the area. Database researchers will benefit from a more complete point of view, including a number of approaches which they may not have focused on within the scope of their own research.

Data Mining Tools for Malware Detection

Data Mining Tools for Malware Detection PDF Author: Mehedy Masud
Publisher: CRC Press
ISBN: 1466516488
Category : Computers
Languages : en
Pages : 453

Book Description
Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level theoretical discussions to the near exclusion of the practical aspects. Breaking the mold, Data Mining Tools for Malware Detection provides a step-by-step breakdown of how to develop data mining tools for malware d

Anomaly Detection and Complex Event Processing Over IoT Data Streams

Anomaly Detection and Complex Event Processing Over IoT Data Streams PDF Author: Patrick Schneider
Publisher: Academic Press
ISBN: 0128238194
Category : Computers
Languages : en
Pages : 408

Book Description
Anomaly Detection and Complex Event Processing over IoT Data Streams: With Application to eHealth and Patient Data Monitoring presents advanced processing techniques for IoT data streams and the anomaly detection algorithms over them. The book brings new advances and generalized techniques for processing IoT data streams, semantic data enrichment with contextual information at Edge, Fog and Cloud as well as complex event processing in IoT applications. The book comprises fundamental models, concepts and algorithms, architectures and technological solutions as well as their application to eHealth. Case studies, such as the bio-metric signals stream processing are presented –the massive amount of raw ECG signals from the sensors are processed dynamically across the data pipeline and classified with modern machine learning approaches including the Hierarchical Temporal Memory and Deep Learning algorithms. The book discusses adaptive solutions to IoT stream processing that can be extended to different use cases from different fields of eHealth, to enable a complex analysis of patient data in a historical, predictive and even prescriptive application scenarios. The book ends with a discussion on ethics, emerging research trends, issues and challenges of IoT data stream processing. - Provides the state-of-the-art in IoT Data Stream Processing, Semantic Data Enrichment, Reasoning and Knowledge - Covers extraction (Anomaly Detection) - Illustrates new, scalable and reliable processing techniques based on IoT stream technologies - Offers applications to new, real-time anomaly detection scenarios in the health domain

Knowledge Discovery from Sensor Data

Knowledge Discovery from Sensor Data PDF Author: Auroop R. Ganguly
Publisher: CRC Press
ISBN: 1420082337
Category : Business & Economics
Languages : en
Pages : 238

Book Description
As sensors become ubiquitous, a set of broad requirements is beginning to emerge across high-priority applications including disaster preparedness and management, adaptability to climate change, national or homeland security, and the management of critical infrastructures. This book presents innovative solutions in offline data mining and real-time