000 04205nam a22003855i 4500
001 387271
003 ES-MaUEC
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008 220601s2019 sz | s |||| 0|eng d
020 _a9783031018671
024 7 _a10.1007/978-3-031-01867-1
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
050 4 _aQA76.9.D3
_b2019
100 1 _aMahmood, Ahmed R
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aScalable Processing of Spatial-Keyword Queries
_cby Ahmed R. Mahmood, Walid G. Aref.
250 _a1st edition 2019
264 1 _aCham
_bSpringer International Publishing
_c2019
300 _a1 recurso en línea (XVII, 98 páginas)
_b
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
490 0 _aSynthesis Lectures on Data Management
_x2153-5426
505 0 _aPreface -- Acknowledgments -- Introduction -- Querying Spatial-Keyword Data -- Centralized Spatial-Keyword Query Processing -- Distributed Spatial-Keyword Processing -- Open Research Problems in Spatial-Keyword Processing -- Bibliography -- Authors' Biographies.
520 _aText 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.
700 1 _aAref, Walid G
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
776 0 8 _iPrinted edition:
_z9783031000942
776 0 8 _iPrinted edition:
_z9783031007392
776 0 8 _iPrinted edition:
_z9783031029950
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01867-1
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
988 _aSynthesis Collection of Technology_2019
999 _c387271
_d387271