Big Data Analytics and Knowledge Discovery : 24th International Conference, DaWaK 2022, Vienna, Austria, August 22–24, 2022, Proceedings / edited by Robert Wrembel, Johann Gamper, Gabriele Kotsis, A Min Tjoa, Ismail Khalil.

Format:

Book

Contributor:

Wrembel, Robert, editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 13428

Language:

English

Subjects (All):

Quantitative research.

Data mining.

Application software.

Artificial intelligence.

Data Analysis and Big Data.

Data Mining and Knowledge Discovery.

Computer and Information Systems Applications.

Artificial Intelligence.

Local Subjects:

Data Analysis and Big Data.

Data Mining and Knowledge Discovery.

Computer and Information Systems Applications.

Artificial Intelligence.

Physical Description:

1 online resource (275 pages)

Edition:

1st ed. 2022.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2022.

Summary:

This volume LNCS 13428 constitutes the papers of the 24 th International Conference on Big Data Analytics and Knowledge Discovery, held in August 2022 in Vienna, Austria. 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.

Contents:

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.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Wrembel, Robert Big Data Analytics and Knowledge Discovery

ISBN:

3-031-12670-X