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Skylines and Other Dominance-Based Queries, Apostolos N. Papadopoulos, Eleftherios Tiakas, Nikolaos Georgiadis, Theodoros Tzouramanis, Yannis Manolopoulos


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Автор: Apostolos N. Papadopoulos, Eleftherios Tiakas, Nikolaos Georgiadis, Theodoros Tzouramanis, Yannis Manolopoulos
Название:  Skylines and Other Dominance-Based Queries
ISBN: 9781681739748
Издательство: Mare Nostrum (Eurospan)
Классификация:




ISBN-10: 1681739747
Обложка/Формат: Hardcover
Страницы: 158
Вес: 0.49 кг.
Дата издания: 30.11.2020
Серия: Synthesis lectures on data management
Язык: English
Размер: 23.50 x 19.10 x 1.12 cm
Читательская аудитория: Professional and scholarly
Ключевые слова: Computer science,Data mining,Information technology: general issues, COMPUTERS / Computer Science,COMPUTERS / Data Processing,COMPUTERS / Databases / Data Mining
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Поставляется из: Англии
Описание: This book is a gentle introduction to dominance-based query processing techniques and their applications. The book aims to present fundamental as well as some advanced issues in the area in a precise, but easy-to-follow, manner. Dominance is an intuitive concept that can be used in many different ways in diverse application domains. The concept of dominance is based on the values of the attributes of each object. An object �� dominates another object �� if �� is better than ��. This goodness criterion may differ from one user to another. However, all decisions boil down to the minimization or maximization of attribute values. In this book, we will explore algorithms and applications related to dominance-based query processing. The concept of dominance has a long history in finance and multi-criteria optimization. However, the introduction of the concept to the database community in 2001 inspired many researchers to contribute to the area. Therefore, many algorithmic techniques have been proposed for the efficient processing of dominance-based queries, such as skyline queries, ��-dominant queries, and top-�� dominating queries, just to name a few.

Scalable Processing of Spatial-Keyword Queries

Автор: Ahmed R. Mahmood, Walid G. Aref
Название: Scalable Processing of Spatial-Keyword Queries
ISBN: 1681734893 ISBN-13(EAN): 9781681734897
Издательство: Mare Nostrum (Eurospan)
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Цена: 72070.00 T
Наличие на складе: Нет в наличии.
Описание: Text data that is associated with location data has become ubiquitous. A tweet is an example of this type of data, where the text in a tweet is associated with the location where the tweet has been issued. We use the term spatial-keyword data to refer to this type of data. Spatial-keyword data is being generated at massive scale. Almost all online transactions have an associated spatial trace. The spatial trace is derived from GPS coordinates, IP addresses, or cell-phone-tower locations. Hundreds of millions or even billions of spatial keyword objects are being generated daily. Spatial-keyword data has numerous applications that require efficient processing and management of massive amounts of spatial-keyword data. This book starts by overviewing some important applications of spatial-keyword data, and demonstrates the scale at which spatial-keyword data is being generated. Then, it formalizes and classifies the various types of queries that execute over spatial-keyword data. Next, it discusses important and desirable properties of spatial-keyword query languages that are needed to express queries over spatial-keyword data. As will be illustrated, existing spatial-keyword query languages vary in the types of spatial-keyword queries that they can support. There are many systems that process spatial-keyword queries. Systems differ from each other in various aspects, e.g., whether the system is batch-oriented or stream-based, and whether the system is centralized or distributed. Moreover, spatial-keyword systems vary in the types of queries that they support. Finally, systems vary in the types of indexing techniques that they adopt. This book provides an overview of the main spatial-keyword data-management systems (SKDMSs), and classifies them according to their features. Moreover, the book describes the main approaches adopted when indexing spatial-keyword data in the centralized and distributed settings. Several case studies of {SKDMSs} are presented along with the applications and query types that these {SKDMSs} are targeted for and the indexing techniques they utilize for processing their queries. Optimizing the performance and the query processing of {SKDMSs} still has many research challenges and open problems. The book concludes with a discussion about several important and open research-problems in the domain of scalable spatial-keyword processing.

Scalable Processing of Spatial-Keyword Queries

Автор: Ahmed R. Mahmood, Walid G. Aref
Название: Scalable Processing of Spatial-Keyword Queries
ISBN: 1681734877 ISBN-13(EAN): 9781681734873
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 51750.00 T
Наличие на складе: Нет в наличии.
Описание: Text data that is associated with location data has become ubiquitous. A tweet is an example of this type of data, where the text in a tweet is associated with the location where the tweet has been issued. We use the term spatial-keyword data to refer to this type of data. Spatial-keyword data is being generated at massive scale. Almost all online transactions have an associated spatial trace. The spatial trace is derived from GPS coordinates, IP addresses, or cell-phone-tower locations. Hundreds of millions or even billions of spatial keyword objects are being generated daily. Spatial-keyword data has numerous applications that require efficient processing and management of massive amounts of spatial-keyword data. This book starts by overviewing some important applications of spatial-keyword data, and demonstrates the scale at which spatial-keyword data is being generated. Then, it formalizes and classifies the various types of queries that execute over spatial-keyword data. Next, it discusses important and desirable properties of spatial-keyword query languages that are needed to express queries over spatial-keyword data. As will be illustrated, existing spatial-keyword query languages vary in the types of spatial-keyword queries that they can support. There are many systems that process spatial-keyword queries. Systems differ from each other in various aspects, e.g., whether the system is batch-oriented or stream-based, and whether the system is centralized or distributed. Moreover, spatial-keyword systems vary in the types of queries that they support. Finally, systems vary in the types of indexing techniques that they adopt. This book provides an overview of the main spatial-keyword data-management systems (SKDMSs), and classifies them according to their features. Moreover, the book describes the main approaches adopted when indexing spatial-keyword data in the centralized and distributed settings. Several case studies of {SKDMSs} are presented along with the applications and query types that these {SKDMSs} are targeted for and the indexing techniques they utilize for processing their queries. Optimizing the performance and the query processing of {SKDMSs} still has many research challenges and open problems. The book concludes with a discussion about several important and open research-problems in the domain of scalable spatial-keyword processing.


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