| TÃtulo : |
23rd International Conference, DaWaK 2021, Virtual Event, September 27–30, 2021, Proceedings |
| Tipo de documento: |
documento electrónico |
| Autores: |
Golfarelli, Matteo, ; Wrembel, Robert, ; Kotsis, Gabriele, ; Tjoa, A Min, ; Khalil, Ismail, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2021 |
| Número de páginas: |
XIII, 282 p. 87 ilustraciones, 73 ilustraciones en color. |
| ISBN/ISSN/DL: |
978-3-030-86534-4 |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Palabras clave: |
Gestión de base de datos Inteligencia artificial Procesamiento de datos Software de la aplicacion Estructuras de datos (Informática) TeorÃa de la información MinerÃa de datos y descubrimiento de conocimientos Aplicaciones informáticas y de sistemas de información Estructuras de datos y teorÃa de la información |
| Ãndice Dewey: |
005.74 Ciencia de los computadores (Archivos de datos y bases de datos) |
| Resumen: |
Este volumen LNCS 12925 constituye los artÃculos de la 23ª Conferencia Internacional sobre Análisis de Big Data y Descubrimiento de Conocimiento, celebrada en septiembre de 2021. Debido a la pandemia de COVID-19, se llevó a cabo de forma virtual. Los 12 artÃculos completos presentados junto con 15 artÃculos breves en este volumen fueron cuidadosamente revisados ​​y seleccionados de un total de 71 presentaciones. Los artÃculos reflejan una amplia gama de temas en el campo de la integración de datos, el almacenamiento de datos, el análisis de datos y, recientemente, el análisis de big data, en un sentido amplio. Los principales objetivos de este evento son explorar, difundir e intercambiar conocimientos en estos campos. |
| Nota de contenido: |
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. |
| En lÃnea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
23rd International Conference, DaWaK 2021, Virtual Event, September 27–30, 2021, Proceedings [documento electrónico] / Golfarelli, Matteo, ; Wrembel, Robert, ; Kotsis, Gabriele, ; Tjoa, A Min, ; Khalil, Ismail, . - 1 ed. . - [s.l.] : Springer, 2021 . - XIII, 282 p. 87 ilustraciones, 73 ilustraciones en color. ISBN : 978-3-030-86534-4 Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
| Palabras clave: |
Gestión de base de datos Inteligencia artificial Procesamiento de datos Software de la aplicacion Estructuras de datos (Informática) TeorÃa de la información MinerÃa de datos y descubrimiento de conocimientos Aplicaciones informáticas y de sistemas de información Estructuras de datos y teorÃa de la información |
| Ãndice Dewey: |
005.74 Ciencia de los computadores (Archivos de datos y bases de datos) |
| Resumen: |
Este volumen LNCS 12925 constituye los artÃculos de la 23ª Conferencia Internacional sobre Análisis de Big Data y Descubrimiento de Conocimiento, celebrada en septiembre de 2021. Debido a la pandemia de COVID-19, se llevó a cabo de forma virtual. Los 12 artÃculos completos presentados junto con 15 artÃculos breves en este volumen fueron cuidadosamente revisados ​​y seleccionados de un total de 71 presentaciones. Los artÃculos reflejan una amplia gama de temas en el campo de la integración de datos, el almacenamiento de datos, el análisis de datos y, recientemente, el análisis de big data, en un sentido amplio. Los principales objetivos de este evento son explorar, difundir e intercambiar conocimientos en estos campos. |
| Nota de contenido: |
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. |
| En lÃnea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
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23rd International Conference, DaWaK 2021, Virtual Event, September 27–30, 2021, Proceedings
