FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2024319164> ?p ?o ?g. }

• W2024319164 endingPage "44" @default.
• W2024319164 startingPage "1" @default.
• W2024319164 abstract "In diverse applications ranging from stock trading to traffic monitoring, data streams are continuously monitored by multiple analysts for extracting patterns of interest in real time. These analysts often submit similar pattern mining requests yet customized with different parameter settings. In this work, we present shared execution strategies for processing a large number of neighbor-based pattern mining requests of the same type yet with arbitrary parameter settings. Such neighbor-based pattern mining requests cover a broad range of popular mining query types, including detection of clusters, outliers, and nearest neighbors. Given the high algorithmic complexity of the mining process, serving multiple such queries in a single system is extremely resource intensive. The naive method of detecting and maintaining patterns for different queries independently is often infeasible in practice, as its demands on system resources increase dramatically with the cardinality of the query workload. In order to maximize the efficiency of the system resource utilization for executing multiple queries simultaneously, we analyze the commonalities of the neighbor-based pattern mining queries, and identify several general optimization principles which lead to significant system resource sharing among multiple queries. In particular, as a preliminary sharing effort, we observe that the computation needed for the range query searches (the process of searching the neighbors for each object) can be shared among multiple queries and thus saves the CPU consumption. Then we analyze the interrelations between the patterns identified by queries with different parameters settings, including both pattern-specific and window-specific parameters. For that, we first introduce an incremental pattern representation, which represents the patterns identified by queries with different pattern-specific parameters within a single compact structure. This enables integrated pattern maintenance for multiple queries. Second, by leveraging the potential overlaps among sliding windows, we propose a metaquery strategy which utilizes a single query to answer multiple queries with different window-specific parameters. By combining these three techniques, namely the range query search sharing, integrated pattern maintenance, and metaquery strategy, our framework realizes fully shared execution of multiple queries with arbitrary parameter settings. It achieves significant savings of computational and memory resources due to shared execution. Our comprehensive experimental study, using real data streams from domains of stock trades and moving object monitoring, demonstrates that our solution is significantly faster than the independent execution strategy, while using only a small portion of memory space compared to the independent execution. We also show that our solution scales in handling large numbers of queries in the order of hundreds or even thousands under high input data rates." @default.
• W2024319164 created "2016-06-24" @default.
• W2024319164 creator A5008269094 @default.
• W2024319164 creator A5010754981 @default.
• W2024319164 creator A5013719632 @default.
• W2024319164 date "2012-02-01" @default.
• W2024319164 modified "2023-09-25" @default.
• W2024319164 title "Shared execution strategy for neighbor-based pattern mining requests over streaming windows" @default.
• W2024319164 cites W1681888921 @default.
• W2024319164 cites W1991482408 @default.
• W2024319164 cites W1994655805 @default.
• W2024319164 cites W2025624833 @default.
• W2024319164 cites W2067914441 @default.
• W2024319164 cites W2077695545 @default.
• W2024319164 cites W2085426673 @default.
• W2024319164 cites W2092335550 @default.
• W2024319164 cites W2093230809 @default.
• W2024319164 cites W2099395665 @default.
• W2024319164 cites W2100832675 @default.
• W2024319164 cites W2101717554 @default.
• W2024319164 cites W2106059185 @default.
• W2024319164 cites W2116300222 @default.
• W2024319164 cites W2124507579 @default.
• W2024319164 cites W2126490564 @default.
• W2024319164 cites W2135499008 @default.
• W2024319164 cites W2144182447 @default.
• W2024319164 cites W2147035797 @default.
• W2024319164 cites W2151369660 @default.
• W2024319164 cites W2169855356 @default.
• W2024319164 cites W4231029117 @default.
• W2024319164 cites W4232534713 @default.
• W2024319164 cites W4247105055 @default.
• W2024319164 doi "https://doi.org/10.1145/2109196.2109201" @default.
• W2024319164 hasPublicationYear "2012" @default.
• W2024319164 type Work @default.
• W2024319164 sameAs 2024319164 @default.
• W2024319164 citedByCount "8" @default.
• W2024319164 countsByYear W20243191642013 @default.
• W2024319164 countsByYear W20243191642016 @default.
• W2024319164 countsByYear W20243191642017 @default.
• W2024319164 countsByYear W20243191642018 @default.
• W2024319164 crossrefType "journal-article" @default.
• W2024319164 hasAuthorship W2024319164A5008269094 @default.
• W2024319164 hasAuthorship W2024319164A5010754981 @default.
• W2024319164 hasAuthorship W2024319164A5013719632 @default.
• W2024319164 hasBestOaLocation W20243191642 @default.
• W2024319164 hasConcept C111919701 @default.
• W2024319164 hasConcept C120314980 @default.
• W2024319164 hasConcept C124101348 @default.
• W2024319164 hasConcept C2778476105 @default.
• W2024319164 hasConcept C41008148 @default.
• W2024319164 hasConcept C87117476 @default.
• W2024319164 hasConcept C89198739 @default.
• W2024319164 hasConcept C98045186 @default.
• W2024319164 hasConceptScore W2024319164C111919701 @default.
• W2024319164 hasConceptScore W2024319164C120314980 @default.
• W2024319164 hasConceptScore W2024319164C124101348 @default.
• W2024319164 hasConceptScore W2024319164C2778476105 @default.
• W2024319164 hasConceptScore W2024319164C41008148 @default.
• W2024319164 hasConceptScore W2024319164C87117476 @default.
• W2024319164 hasConceptScore W2024319164C89198739 @default.
• W2024319164 hasConceptScore W2024319164C98045186 @default.
• W2024319164 hasFunder F4320337387 @default.
• W2024319164 hasFunder F4320337389 @default.
• W2024319164 hasIssue "1" @default.
• W2024319164 hasLocation W20243191641 @default.
• W2024319164 hasLocation W20243191642 @default.
• W2024319164 hasOpenAccess W2024319164 @default.
• W2024319164 hasPrimaryLocation W20243191641 @default.
• W2024319164 hasRelatedWork W1531525233 @default.
• W2024319164 hasRelatedWork W1911446530 @default.
• W2024319164 hasRelatedWork W2115354953 @default.
• W2024319164 hasRelatedWork W2163397365 @default.
• W2024319164 hasRelatedWork W2336391106 @default.
• W2024319164 hasRelatedWork W2907151469 @default.
• W2024319164 hasRelatedWork W3093672812 @default.
• W2024319164 hasRelatedWork W811092902 @default.
• W2024319164 hasRelatedWork W950522295 @default.
• W2024319164 hasRelatedWork W2080337565 @default.
• W2024319164 hasVolume "37" @default.
• W2024319164 isParatext "false" @default.
• W2024319164 isRetracted "false" @default.
• W2024319164 magId "2024319164" @default.
• W2024319164 workType "article" @default.