000 04611nam a22005175i 4500
001 978-3-031-01867-1
003 DE-He213
005 20240730163736.0
007 cr nn 008mamaa
008 220601s2019 sz | s |||| 0|eng d
020 _a9783031018671
_9978-3-031-01867-1
024 7 _a10.1007/978-3-031-01867-1
_2doi
050 4 _aTK5105.5-5105.9
072 7 _aUKN
_2bicssc
072 7 _aCOM043000
_2bisacsh
072 7 _aUKN
_2thema
082 0 4 _a004.6
_223
100 1 _aMahmood, Ahmed R.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980315
245 1 0 _aScalable Processing of Spatial-Keyword Queries
_h[electronic resource] /
_cby Ahmed R. Mahmood, Walid G. Aref.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXVII, 98 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _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 presentedalong 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.
650 0 _aComputer networks .
_931572
650 0 _aData structures (Computer science).
_98188
650 0 _aInformation theory.
_914256
650 1 4 _aComputer Communication Networks.
_980316
650 2 4 _aData Structures and Information Theory.
_931923
700 1 _aAref, Walid G.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980317
710 2 _aSpringerLink (Online service)
_980318
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031000942
776 0 8 _iPrinted edition:
_z9783031007392
776 0 8 _iPrinted edition:
_z9783031029950
830 0 _aSynthesis Lectures on Data Management,
_x2153-5426
_980319
856 4 0 _uhttps://doi.org/10.1007/978-3-031-01867-1
912 _aZDB-2-SXSC
942 _cEBK
999 _c84937
_d84937