This volume LNCS 12925 constitutes the papers of the 23rd International Conference on Big Data Analytics and Knowledge Discovery, held in September 2021. Due to COVID-19 pandemic it was held virtually.
The 12 full papers presented together with 15 short papers in this volume were carefully reviewed and selected from a total of 71 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.
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Illustrationen
73
14 s/w Abbildungen, 73 farbige Abbildungen
XIII, 282 p. 87 illus., 73 illus. in color.
ISBN-13
978-3-030-86534-4 (9783030865344)
DOI
10.1007/978-3-030-86534-4
Schweitzer Klassifikation
Performance.- Bounding Box Representation of Co-Location Instances for L-infinity Induced Distance Measure.- Benchmarking Data Lakes Featuring Structured and Unstructured Data with DLBench.- Towards an Adaptive Multidimensional Partitioning for Accelerating Spark SQL.- Selecting Subexpressions to Materialize for Dynamic Large-scale Workloads.- Prediction Techniques.- A Chain Composite Item Recommender for Lifelong Pathways.- Health Analytics on COVID-19 Data with Few-Shot Learning.- Cognitive Visual Commonsense Reasoning Using Dynamic Working Memory.- Knowledge Representation.- Universal Storage Adaption for Distributed RDF-triple Stores.- RDF Data Management is an Analytical Market, not a Transaction one.- Document Ranking for Curated Document Databases using BERT and Knowledge Graph Embeddings: Introducing GRAB-Rank.- Advanced Analytics.- Contextual and Behavior Factors Extraction from Pedestrian Encounter Scenes Using Deep Language Models.- Spark based Text Clustering Method using Hashing.- Impact of textual data augmentation on linguistic pattern extraction to improve the idiomaticity of extractive summaries.- Explainability in Irony Detection.- Efficient Graph Analytics in Python for Large-scale Data Science.- Machine Learning and Deep Learning.- A New Accurate Clustering Approach for Detecting Different Densities in High Dimensional Data.- ODCA: an Outlier Detection Approach to Deal with Correlated Attributes.- A Novel Neurofuzzy Approach for Semantic Similarity Measurement.- Data Warehouse Processes and Maintenance.- Integrated Process Data and Organizational Data Analysis for Business Process Improvement.- Smart-Views: Decentralized OLAP View Management using Blockchains.- A workload-aware change data capture framework for data warehousing.- Machine Learning and Analtyics.- Motif Based Feature Vectors: Towards a Homogeneous Data Representation for Cardiovascular Diseases Classification.- Filter-based Feature Selection Methods for Industrial Sensor Data: A Review.- A Declarative Framework for mining Top-k High Utility Itemsets.- Multi-label Feature Selection Algorithm via Maximizing Label Correlation-aware Relevance and Minimizing Redundance with Mutation Binary Particle Swarm Optimization.- Mining Partially-Ordered Episode Rules with the Head Support.- Boosting Latent Inference of Resident Preference from Electricity Usage - A Demonstration on Online Advertisement Strategies.
