Big Data Analytics and Knowledge Discovery
Springer International Publishing (Verlag)
978-3-031-12669-7 (ISBN)
The 12 full papers presented together with 12 short papers in this volume were carefully reviewed and selected from a total of 57 submissions.
The papers reflect a wide range of topics in the field of data integration, data warehousing, data analytics, and recently big data analytics, in a broad sense. The main objectives of this event are to explore, disseminate, and exchange knowledge in these fields.
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.
| Erscheinungsdatum | 27.07.2022 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | XIII, 272 p. 79 illus., 60 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 444 g |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Schlagworte | Applications • Artificial Intelligence • Big Data • Computer Hardware • Computer Networks • Computer Science • Computer systems • conference proceedings • Correlation Analysis • Databases • Data Mining • digital storage • Education • Engineering • Informatics • Information Management • Internet • Knowledge-Based System • learning • machine learning • Mathematics • Research • Signal Processing • World Wide Web |
| ISBN-10 | 3-031-12669-6 / 3031126696 |
| ISBN-13 | 978-3-031-12669-7 / 9783031126697 |
| Zustand | Neuware |
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