Produktbild: Big Data Analytics and Knowledge Discovery
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Big Data Analytics and Knowledge Discovery 24th International Conference, DaWaK 2022, Vienna, Austria, August 22–24, 2022, Proceedings

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

26.07.2022

Herausgeber

Robert Wrembel + weitere

Verlag

Springer

Seitenzahl

272

Maße (L/B/H)

23,5/15,5/1,6 cm

Gewicht

441 g

Auflage

1st ed. 2022

Sprache

Englisch

ISBN

978-3-031-12669-7

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

26.07.2022

Herausgeber

Verlag

Springer

Seitenzahl

272

Maße (L/B/H)

23,5/15,5/1,6 cm

Gewicht

441 g

Auflage

1st ed. 2022

Sprache

Englisch

ISBN

978-3-031-12669-7

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Big Data Analytics and Knowledge Discovery
  • An Integration of TextGCN and Autoencoder into Aspect-based Sentiment Analysis.- OpBerg: Discovering causal sentences using optimal alignments.- Text-based Causal Inference on Irony and Sarcasm Detection.- Sarcastic RoBERTa: a RoBERTa-based deep neural network detecting sarcasm on Twitter.- A Fast NDFA-Based Approach to Approximate Pattern-Matching for Plagiarism Detection in Blockchain-Driven NFTs.- On Decisive Skyline Queries.- Safeness: Suffix Arrays driven Materialized View Selection Framework for Large-Scale Workloads.- A Process Warehouse for Process Variants Analysis.- Feature Selection Algorithms.- Unsupervised Features Ranking via Coalitional Game Theory for Categorical Data.- Multi-label Online Streaming Feature Selection Algorithms via Extending Alpha Investing Strategy.- Feature Selection Under Fairness and Performance Constraints.- Time Series Processing.- Interpretable Input-Output Hidden Markov Model-Based Deep Reinforcement Learning for the Predictive Maintenance of Turbofan Engines.- Pathology Data Prioritisation: A Study Using Multi-Variate Time Series.- Outlier/Anomaly detection of univariate time series: A dataset collection and benchmark.- Automatic Machine Learning-based OLAP Measure Detection for Tabular Data.- Discovering Overlapping Communities based on Cohesive Subgraph Models over Graph Data.- Discovery of Keys for Graphs.- OPTIMA: Framework Selecting Optimal Virtual Model to Query Large Heterogeneous Data.- . Q-VIPER: Quantitative Vertical Bitwise Algorithm to Mine Frequent Patterns.- Enhanced Sliding Window-Based Periodic Pattern Mining from Dynamic Streams.- Explainable Recommendations for Wearable Sensor Data Machine Learning.- SLA-Aware Cloud Query Processing with Reinforcement Learning-based MultiObjective Re-Optimization.- Distance Based K-Means Clustering.- Grapevine Phenology Prediction: A Comparison of Physical and Machine Learning Models.