Matches in SemOpenAlex for { <https://semopenalex.org/work/W2903551170> ?p ?o ?g. }
- W2903551170 startingPage "21" @default.
- W2903551170 abstract "Pattern matching is a powerful graph analysis tool. Unfortunately, existing solutions have limited scalability, support only a limited set of search patterns, and/or focus on only a subset of the real-world problems associated with pattern matching. This paper presents a new algorithmic pipeline that: (i) enables highly scalable pattern matching on labeled graphs, (ii) supports arbitrary patterns, (iii) enables trade-offs between precision and time-to-solution (while always selecting all vertices and edges that participate in matches, thus offering 100% recall), and (iv) supports a set of popular data analytics scenarios. We implement our approach on top of HavoqGT and demonstrate its advantages through strong and weak scaling experiments on massive-scale real-world (up to 257 billion edges) and synthetic (up to 4.4 trillion edges) graphs, respectively, and at scales (1,024 nodes / 36,864 cores) orders of magnitude larger than used in the past for similar problems." @default.
- W2903551170 created "2018-12-11" @default.
- W2903551170 creator A5043238877 @default.
- W2903551170 creator A5046256174 @default.
- W2903551170 creator A5088755273 @default.
- W2903551170 creator A5089134354 @default.
- W2903551170 creator A5091074171 @default.
- W2903551170 date "2018-11-11" @default.
- W2903551170 modified "2023-09-28" @default.
- W2903551170 title "PruneJuice: pruning trillion-edge graphs to a precise pattern-matching solution" @default.
- W2903551170 cites W144764141 @default.
- W2903551170 cites W1448681276 @default.
- W2903551170 cites W1482680420 @default.
- W2903551170 cites W1783256592 @default.
- W2903551170 cites W1794858913 @default.
- W2903551170 cites W1990600049 @default.
- W2903551170 cites W1996229963 @default.
- W2903551170 cites W2035173902 @default.
- W2903551170 cites W2042639302 @default.
- W2903551170 cites W2048653843 @default.
- W2903551170 cites W2056524360 @default.
- W2903551170 cites W2068612205 @default.
- W2903551170 cites W2081385143 @default.
- W2903551170 cites W2085494605 @default.
- W2903551170 cites W2098817244 @default.
- W2903551170 cites W2102039892 @default.
- W2903551170 cites W2109294083 @default.
- W2903551170 cites W2110942501 @default.
- W2903551170 cites W2118212234 @default.
- W2903551170 cites W2118893477 @default.
- W2903551170 cites W2119995149 @default.
- W2903551170 cites W2120593471 @default.
- W2903551170 cites W2123916114 @default.
- W2903551170 cites W2123966888 @default.
- W2903551170 cites W2126359798 @default.
- W2903551170 cites W2128853364 @default.
- W2903551170 cites W2130904350 @default.
- W2903551170 cites W2135764373 @default.
- W2903551170 cites W2140840007 @default.
- W2903551170 cites W2147094350 @default.
- W2903551170 cites W2147405597 @default.
- W2903551170 cites W2148268260 @default.
- W2903551170 cites W2157207306 @default.
- W2903551170 cites W2167429959 @default.
- W2903551170 cites W2170616854 @default.
- W2903551170 cites W2250844151 @default.
- W2903551170 cites W2286580204 @default.
- W2903551170 cites W2296407087 @default.
- W2903551170 cites W2412465557 @default.
- W2903551170 cites W2491983741 @default.
- W2903551170 cites W2505011268 @default.
- W2903551170 cites W2621740759 @default.
- W2903551170 cites W2757008478 @default.
- W2903551170 cites W2758273103 @default.
- W2903551170 cites W78077100 @default.
- W2903551170 doi "https://doi.org/10.5555/3291656.3291684" @default.
- W2903551170 hasPublicationYear "2018" @default.
- W2903551170 type Work @default.
- W2903551170 sameAs 2903551170 @default.
- W2903551170 citedByCount "7" @default.
- W2903551170 countsByYear W29035511702018 @default.
- W2903551170 countsByYear W29035511702019 @default.
- W2903551170 countsByYear W29035511702020 @default.
- W2903551170 countsByYear W29035511702021 @default.
- W2903551170 crossrefType "proceedings-article" @default.
- W2903551170 hasAuthorship W2903551170A5043238877 @default.
- W2903551170 hasAuthorship W2903551170A5046256174 @default.
- W2903551170 hasAuthorship W2903551170A5088755273 @default.
- W2903551170 hasAuthorship W2903551170A5089134354 @default.
- W2903551170 hasAuthorship W2903551170A5091074171 @default.
- W2903551170 hasConcept C105795698 @default.
- W2903551170 hasConcept C108010975 @default.
- W2903551170 hasConcept C11413529 @default.
- W2903551170 hasConcept C120665830 @default.
- W2903551170 hasConcept C121332964 @default.
- W2903551170 hasConcept C124101348 @default.
- W2903551170 hasConcept C132525143 @default.
- W2903551170 hasConcept C154945302 @default.
- W2903551170 hasConcept C162307627 @default.
- W2903551170 hasConcept C165064840 @default.
- W2903551170 hasConcept C177264268 @default.
- W2903551170 hasConcept C192209626 @default.
- W2903551170 hasConcept C199360897 @default.
- W2903551170 hasConcept C2524010 @default.
- W2903551170 hasConcept C33923547 @default.
- W2903551170 hasConcept C41008148 @default.
- W2903551170 hasConcept C43521106 @default.
- W2903551170 hasConcept C48044578 @default.
- W2903551170 hasConcept C6557445 @default.
- W2903551170 hasConcept C68859911 @default.
- W2903551170 hasConcept C77088390 @default.
- W2903551170 hasConcept C79158427 @default.
- W2903551170 hasConcept C80444323 @default.
- W2903551170 hasConcept C86803240 @default.
- W2903551170 hasConcept C99844830 @default.
- W2903551170 hasConceptScore W2903551170C105795698 @default.
- W2903551170 hasConceptScore W2903551170C108010975 @default.
- W2903551170 hasConceptScore W2903551170C11413529 @default.
- W2903551170 hasConceptScore W2903551170C120665830 @default.