國立虎尾科技大學 |

Scalable processing of spatial-keyword queries /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Scalable processing of spatial-keyword queries // Ahmed R. Mahmood and Walid G. Aref.
Author:	Mahmood, Ahmed R.,
other author:	Aref, Walid G.,
Description:	1 PDF (xvii, 98 pages) :illustrations. :
Notes:	Part of: Synthesis digital library of engineering and computer science.
Subject:	Querying (Computer science) -
Online resource:	https://ieeexplore.ieee.org/servlet/opac?bknumber=8638927
ISBN:	9781681734880

Scalable processing of spatial-keyword queries /
Mahmood, Ahmed R.,

Scalable processing of spatial-keyword queries /Ahmed R. Mahmood and Walid G. Aref. - 1 PDF (xvii, 98 pages) :illustrations. - Synthesis lectures on data management,# 562153-5426 ;. - Synthesis digital library of engineering and computer science..

Part of: Synthesis digital library of engineering and computer science.

Includes bibliographical references (pages 77-95).

1. Introduction -- 1.1 Spatial-keyword data -- 1.2 Spatial-keyword applications --

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

Compendex

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.

Mode of access: World Wide Web.

ISBN: 9781681734880

Standard No.: 10.2200/S00892ED1V01Y201901DTM056doiSubjects--Topical Terms:

785780
Querying (Computer science)
Subjects--Index Terms:

big data

LC Class. No.: QA76.9.D3 / M247 2019

Dewey Class. No.: 005.7565

Scalable processing of spatial-keyword queries /
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020 $z 9781681734897 $q hardcover
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245 1 0 $a Scalable processing of spatial-keyword queries / $c Ahmed R. Mahmood and Walid G. Aref.
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300 $a 1 PDF (xvii, 98 pages) : $b illustrations.
336 $a text $2 rdacontent
337 $a electronic $2 isbdmedia
338 $a online resource $2 rdacarrier
490 1 $a Synthesis lectures on data management, $x 2153-5426 ; $v # 56
500 $a Part of: Synthesis digital library of engineering and computer science.
504 $a Includes bibliographical references (pages 77-95).
505 0 $a 1. Introduction -- 1.1 Spatial-keyword data -- 1.2 Spatial-keyword applications --
505 8 $a 2. Querying spatial-keyword data -- 2.1 Spatial-keyword query predicates -- 2.1.1 The spatial-keyword select predicate -- 2.1.2 The spatial-keyword join predicates -- 2.1.3 The spatial-keyword group predicate -- 2.1.4 Continuous spatial-keyword queries -- 2.1.5 Aggregate spatial-keyword predicates -- 2.1.6 Distance metrics in spatial-keyword predicates -- 2.2 Spatial-keyword query languages -- 2.2.1 GNIP -- 2.2.2 Microblogs query language (MQL) -- 2.2.3 Atlas --
505 8 $a 3. Centralized spatial-keyword query processing -- 3.1 Spatial indexing -- 3.1.1 Space-driven indexes -- 3.1.2 Data-driven spatial indexes -- 3.2 Text indexes -- 3.3 Spatial-keyword indexes -- 3.3.1 Space-first spatial-keyword indexing -- 3.3.2 Text-first indexing -- 3.3.3 Interleaved spatial-keyword indexing -- 3.3.4 Separate spatial and keyword indexes -- 3.3.5 Spatiotemporal-keyword indexing -- 3.4 Case studies --
505 8 $a 4. Distributed spatial-keyword processing -- 4.1 General-purpose big-data systems -- 4.1.1 Batch-oriented systems -- 4.1.2 Big-data streaming systems -- 4.2 Big spatial-keyword data management systems -- 4.2.1 Application on top of existing big-data system -- 4.2.2 Extension to general-purpose big-data systems -- 4.2.3 Dedicated big spatial-keyword data management systems -- 4.3 Strategies to distribute and index data in big SKDMSs -- 4.3.1 Spatial-only indexing -- 4.3.2 Hash-based indexing -- 4.3.3 Hybrid indexing -- 4.3.4 Partitioning of spatial-keyword data streams -- 4.4 Case studies --
505 8 $a 5. Open research problems in spatial-keyword processing -- 5.1 Load balancing -- 5.2 Spatial-keyword benchmarks -- 5.3 Spatial-keyword query optimizer -- 5.4 Big spatio-temporal keyword query processing --
505 8 $a Bibliography -- Authors' biographies.
506 $a Abstract freely available; full-text restricted to subscribers or individual document purchasers.
510 0 $a Compendex
510 0 $a INSPEC
510 0 $a Google scholar
510 0 $a Google book search
520 3 $a 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.
530 $a Also available in print.
538 $a Mode of access: World Wide Web.
538 $a System requirements: Adobe Acrobat Reader.
588 $a Title from PDF title page (viewed on February 26, 2019).
650 0 $a Querying (Computer science) $3 785780
650 0 $a Keyword searching. $3 841006
650 0 $a Spatial data infrastructures. $3 682258
653 $a big data
653 $a query processing
653 $a spatial-keyword
653 $a indexing
653 $a systems
700 1 $a Aref, Walid G., $e author. $3 1253056
776 0 8 $i Print version: $z 9781681734897 $z 9781681734873
830 0 $a Synthesis digital library of engineering and computer science. $3 598254
830 0 $a Synthesis lectures on data management ; $v #36. $3 931356
856 4 2 $3 Abstract with links to resource $u https://ieeexplore.ieee.org/servlet/opac?bknumber=8638927