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Ontology type: schema:Periodical     


Journal Info

START YEAR

1999

PUBLISHER

Springer Vienna

LANGUAGE

en

HOMEPAGE

http://link.springer.com/journal/607

Recent publications latest 20 shown

  • 2019-04-12 Batch activity: enhancing business process modeling and enactment with batch processing
  • 2019-04-11 A mosaic method for multi-temporal data registration by using convolutional neural networks for forestry remote sensing applications
  • 2019-04 Area coverage of heterogeneous wireless sensor networks in support of Internet of Things demands
  • 2019-04 Multivariate network traffic analysis using clustered patterns
  • 2019-04 Performance evaluation of TCP-BIAD in high-speed, long-distance networks
  • 2019-04 On personalized cloud service provisioning for mobile users using adaptive and context-aware service composition
  • 2019-03-29 Efficient techniques of parallel recovery for erasure-coding-based distributed file systems
  • 2019-03-27 Hinode: implementing a vertex-centric modelling approach to maintaining historical graph data
  • 2019-03-26 RNN-based signal classification for hybrid audio data compression
  • 2019-03-12 Multidimensional scaling method for prediction of lysine glycation sites
  • 2019-03-12 Bulk-loading and bulk-insertion algorithms for xBR+-trees in Solid State Drives
  • 2019-03-08 A location-sensitive and network-aware broker for recommending Web services
  • 2019-03 A predictive load balancing technique for software defined networked cloud services
  • 2019-03 Logs and enterprise networks for overcoming obstacles in business processes
  • 2019-03 Crowdsourcing planar facility location allocation problems
  • 2019-03 gat2vec: representation learning for attributed graphs
  • 2019-03 Correction to: Inverse formulas of parameterized orthogonal wavelets
  • 2019-02-27 Personalized detection of lane changing behavior using multisensor data fusion
  • 2019-02-18 Homomorphically encrypted k-means on cloud-hosted servers with low client-side load
  • 2019-02-13 Interpretation and automatic integration of geospatial data into the Semantic Web
  • JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

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