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008 220601s2018 sz | s |||| 0|eng d
020 _a9783031018602
_9978-3-031-01860-2
024 7 _a10.1007/978-3-031-01860-2
_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 _aKhan, Arijit.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980297
245 1 0 _aOn Uncertain Graphs
_h[electronic resource] /
_cby Arijit Khan, Yuan Ye, Lei Chen.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXIII, 80 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 _aAcknowledgments -- Introduction to Uncertain Graphs -- Reliability Queries -- Graph Pattern Matching Queries -- Graph Similarity Search Queries -- Influence Maximization -- Major Open Problems -- Bibliography -- Authors' Biographies .
520 _aLarge-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasize the current challenges and highlight some future research directions.
650 0 _aComputer networks .
_931572
650 0 _aData structures (Computer science).
_98188
650 0 _aInformation theory.
_914256
650 1 4 _aComputer Communication Networks.
_980298
650 2 4 _aData Structures and Information Theory.
_931923
700 1 _aYe, Yuan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980299
700 1 _aChen, Lei.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980300
710 2 _aSpringerLink (Online service)
_980301
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031000874
776 0 8 _iPrinted edition:
_z9783031007323
776 0 8 _iPrinted edition:
_z9783031029882
830 0 _aSynthesis Lectures on Data Management,
_x2153-5426
_980302
856 4 0 _uhttps://doi.org/10.1007/978-3-031-01860-2
912 _aZDB-2-SXSC
942 _cEBK
999 _c84934
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