Big Data Analytics and Knowledge Discovery by Matteo Golfarelli
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Big Data Analytics and Knowledge Discovery

Big Data Analytics and Knowledge Discovery


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About the Book

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.


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Product Details
  • ISBN-13: 9783030865337
  • Publisher: Springer Nature Switzerland AG
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: 23rd International Conference, Dawak 2021, Virtual Event, September 27-30, 2021, Proceedings
  • Width: 156 mm
  • ISBN-10: 3030865339
  • Publisher Date: 05 Sep 2021
  • Height: 234 mm
  • No of Pages: 298
  • Spine Width: 16 mm
  • Weight: 471 gr


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