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Autor Tjoa, A Min |
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Big Data Analytics and Knowledge Discovery / Ordonez, Carlos ; Song, Il-Yeol ; Anderst-Kotsis, Gabriele ; Tjoa, A Min ; Khalil, Ismail
TÃtulo : Big Data Analytics and Knowledge Discovery : 21st International Conference, DaWaK 2019, Linz, Austria, August 26–29, 2019, Proceedings / Tipo de documento: documento electrónico Autores: Ordonez, Carlos, ; Song, Il-Yeol, ; Anderst-Kotsis, Gabriele, ; Tjoa, A Min, ; Khalil, Ismail, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2019 Número de páginas: XIII, 321 p. 164 ilustraciones, 80 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-27520-4 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Gestión de base de datos Procesamiento de datos Unidades aritméticas y lógicas informáticas. Computadoras digitales electrónicas Inteligencia artificial MinerÃa de datos y descubrimiento de conocimientos Estructuras aritméticas y lógicas Rendimiento y evaluación del sistema Clasificación: 005.74 Ciencia de los computadores (Archivos de datos y bases de datos) Resumen: Este libro constituye las actas arbitradas de la 21.ª Conferencia Internacional sobre Análisis de Big Data y Descubrimiento de Conocimiento, DaWaK 2019, celebrada en Linz, Austria, en septiembre de 2019. Los 12 artÃculos completos y 10 artÃculos breves presentados fueron cuidadosamente revisados ​​y seleccionados entre 61 presentaciones. Los artÃculos están organizados en las siguientes secciones temáticas: Aplicaciones; patrones; RDF y corrientes; sistemas de grandes datos; gráficos y aprendizaje automático; bases de datos. Nota de contenido: Applications -- Detecting the Onset of Machine Failure Using Anomaly Detection Methods -- A Hybrid Architecture for Tactical and Strategic Precision Agriculture -- Urban analytics of big transportation data for supporting smart cities -- Patterns -- Frequent Item Mining When Obtaining Support is Costly -- Mining Sequential Pattern of Historical Purchases for E-Commerce Recommendation -- Discovering and Visualizing Efficient Patterns in Cost/Utility Sequences -- Efficient Row Pattern Matching using Pattern Hierarchies for Sequence OLAP -- Statistically Significant Discriminative Patterns Searching -- RDF and Streams -- Multidimensional Integration of RDF datasets -- RDFPartSuite: Bridging Physical and Logical RDF Partitioning -- Mining quantitative temporal dependencies between interval-based streams -- Democratization of OLAP DSMS -- Big Data Systems -- Leveraging the Data Lake - Current State and Challenges -- SDWP: A New Data Placement Strategy for Distributed Big DataWarehouses in Hadoop -- Improved Programming-Language Independent MapReduce on Shared-Memory Systems -- Evaluating Redundancy and Partitioning of Geospatial Data in Document-Oriented Data Warehouses -- Graphs and Machine Learning -- Scalable Least Square Twin Support Vector Machine Learning -- Finding Strongly Correlated Trends in Dynamic Attributed Graphs -- Text-based Event Detection: Deciphering Date Information Using Graph Embeddings -- Efficiently Computing Homomorphic Matches of Hybrid Pattern Queries on Large Graphs -- Databases -- From Conceptual to Logical ETL Design using BPMN and Relational Algebra -- Accurate Aggregation Query-Result Estimation and Its Efficient Processing on Distributed Key-Value Store. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 21st International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2019, held in Linz, Austria, in September 2019. The 12 full papers and 10 short papers presented were carefully reviewed and selected from 61 submissions. The papers are organized in the following topical sections: Applications; patterns; RDF and streams; big data systems; graphs and machine learning; databases. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Big Data Analytics and Knowledge Discovery : 21st International Conference, DaWaK 2019, Linz, Austria, August 26–29, 2019, Proceedings / [documento electrónico] / Ordonez, Carlos, ; Song, Il-Yeol, ; Anderst-Kotsis, Gabriele, ; Tjoa, A Min, ; Khalil, Ismail, . - 1 ed. . - [s.l.] : Springer, 2019 . - XIII, 321 p. 164 ilustraciones, 80 ilustraciones en color.
ISBN : 978-3-030-27520-4
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Gestión de base de datos Procesamiento de datos Unidades aritméticas y lógicas informáticas. Computadoras digitales electrónicas Inteligencia artificial MinerÃa de datos y descubrimiento de conocimientos Estructuras aritméticas y lógicas Rendimiento y evaluación del sistema Clasificación: 005.74 Ciencia de los computadores (Archivos de datos y bases de datos) Resumen: Este libro constituye las actas arbitradas de la 21.ª Conferencia Internacional sobre Análisis de Big Data y Descubrimiento de Conocimiento, DaWaK 2019, celebrada en Linz, Austria, en septiembre de 2019. Los 12 artÃculos completos y 10 artÃculos breves presentados fueron cuidadosamente revisados ​​y seleccionados entre 61 presentaciones. Los artÃculos están organizados en las siguientes secciones temáticas: Aplicaciones; patrones; RDF y corrientes; sistemas de grandes datos; gráficos y aprendizaje automático; bases de datos. Nota de contenido: Applications -- Detecting the Onset of Machine Failure Using Anomaly Detection Methods -- A Hybrid Architecture for Tactical and Strategic Precision Agriculture -- Urban analytics of big transportation data for supporting smart cities -- Patterns -- Frequent Item Mining When Obtaining Support is Costly -- Mining Sequential Pattern of Historical Purchases for E-Commerce Recommendation -- Discovering and Visualizing Efficient Patterns in Cost/Utility Sequences -- Efficient Row Pattern Matching using Pattern Hierarchies for Sequence OLAP -- Statistically Significant Discriminative Patterns Searching -- RDF and Streams -- Multidimensional Integration of RDF datasets -- RDFPartSuite: Bridging Physical and Logical RDF Partitioning -- Mining quantitative temporal dependencies between interval-based streams -- Democratization of OLAP DSMS -- Big Data Systems -- Leveraging the Data Lake - Current State and Challenges -- SDWP: A New Data Placement Strategy for Distributed Big DataWarehouses in Hadoop -- Improved Programming-Language Independent MapReduce on Shared-Memory Systems -- Evaluating Redundancy and Partitioning of Geospatial Data in Document-Oriented Data Warehouses -- Graphs and Machine Learning -- Scalable Least Square Twin Support Vector Machine Learning -- Finding Strongly Correlated Trends in Dynamic Attributed Graphs -- Text-based Event Detection: Deciphering Date Information Using Graph Embeddings -- Efficiently Computing Homomorphic Matches of Hybrid Pattern Queries on Large Graphs -- Databases -- From Conceptual to Logical ETL Design using BPMN and Relational Algebra -- Accurate Aggregation Query-Result Estimation and Its Efficient Processing on Distributed Key-Value Store. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 21st International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2019, held in Linz, Austria, in September 2019. The 12 full papers and 10 short papers presented were carefully reviewed and selected from 61 submissions. The papers are organized in the following topical sections: Applications; patterns; RDF and streams; big data systems; graphs and machine learning; databases. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Big Data Analytics and Knowledge Discovery / Song, Min ; Song, Il-Yeol ; Kotsis, Gabriele ; Tjoa, A Min ; Khalil, Ismail
TÃtulo : Big Data Analytics and Knowledge Discovery : 22nd International Conference, DaWaK 2020, Bratislava, Slovakia, September 14–17, 2020, Proceedings / Tipo de documento: documento electrónico Autores: Song, Min, ; Song, Il-Yeol, ; Kotsis, Gabriele, ; Tjoa, A Min, ; Khalil, Ismail, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2020 Número de páginas: XIII, 410 p. 153 ilustraciones, 113 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-59065-9 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Gestión de base de datos TecnologÃa de la información Ciencias sociales Sistemas informáticos Sistemas de almacenamiento y recuperación de información. Aplicación Informática en Tratamiento de Datos Administrativos Aplicación informática en ciencias sociales y del comportamiento. Computadoras y Educación Implementación de sistema informático Almacenamiento y recuperación de información Clasificación: 005.74 Ciencia de los computadores (Archivos de datos y bases de datos) Resumen: El volumen LNCS 12393 constituye los artÃculos de la 22ª Conferencia Internacional Big Data Analytics and Knowledge Discovery que se llevará a cabo en lÃnea en septiembre de 2020. Los 15 artÃculos completos presentados junto con 14 artÃculos breves más 1 artÃculo de posición en este volumen fueron cuidadosamente revisados ​​y seleccionados de un total de 77 presentaciones. Este volumen ofrece una amplia gama de temas siguientes sobre aspectos teóricos y prácticos del análisis de big data y el descubrimiento de conocimientos como una nueva generación de repositorios de big data, preprocesamiento de datos, minerÃa de datos, minerÃa de textos, secuencias, minerÃa de gráficos y procesamiento paralelo. Nota de contenido: Big data -- Knowledge Discovery -- Query Languages -- Artificial Intelligent.-Machine Learning -- Data Warehousing -- Distributed System -- Visualization -- Data Management -- Multimedia Data. . Tipo de medio : Computadora Summary : The volume LNCS 12393 constitutes the papers of the 22nd International Conference Big Data Analytics and Knowledge Discovery which will be held online in September 2020. The 15 full papers presented together with 14 short papers plus 1 position paper in this volume were carefully reviewed and selected from a total of 77 submissions. This volume offers a wide range to following subjects on theoretical and practical aspects of big data analytics and knowledge discovery as a new generation of big data repository, data pre-processing, data mining, text mining, sequences, graph mining, and parallel processing. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Big Data Analytics and Knowledge Discovery : 22nd International Conference, DaWaK 2020, Bratislava, Slovakia, September 14–17, 2020, Proceedings / [documento electrónico] / Song, Min, ; Song, Il-Yeol, ; Kotsis, Gabriele, ; Tjoa, A Min, ; Khalil, Ismail, . - 1 ed. . - [s.l.] : Springer, 2020 . - XIII, 410 p. 153 ilustraciones, 113 ilustraciones en color.
ISBN : 978-3-030-59065-9
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Gestión de base de datos TecnologÃa de la información Ciencias sociales Sistemas informáticos Sistemas de almacenamiento y recuperación de información. Aplicación Informática en Tratamiento de Datos Administrativos Aplicación informática en ciencias sociales y del comportamiento. Computadoras y Educación Implementación de sistema informático Almacenamiento y recuperación de información Clasificación: 005.74 Ciencia de los computadores (Archivos de datos y bases de datos) Resumen: El volumen LNCS 12393 constituye los artÃculos de la 22ª Conferencia Internacional Big Data Analytics and Knowledge Discovery que se llevará a cabo en lÃnea en septiembre de 2020. Los 15 artÃculos completos presentados junto con 14 artÃculos breves más 1 artÃculo de posición en este volumen fueron cuidadosamente revisados ​​y seleccionados de un total de 77 presentaciones. Este volumen ofrece una amplia gama de temas siguientes sobre aspectos teóricos y prácticos del análisis de big data y el descubrimiento de conocimientos como una nueva generación de repositorios de big data, preprocesamiento de datos, minerÃa de datos, minerÃa de textos, secuencias, minerÃa de gráficos y procesamiento paralelo. Nota de contenido: Big data -- Knowledge Discovery -- Query Languages -- Artificial Intelligent.-Machine Learning -- Data Warehousing -- Distributed System -- Visualization -- Data Management -- Multimedia Data. . Tipo de medio : Computadora Summary : The volume LNCS 12393 constitutes the papers of the 22nd International Conference Big Data Analytics and Knowledge Discovery which will be held online in September 2020. The 15 full papers presented together with 14 short papers plus 1 position paper in this volume were carefully reviewed and selected from a total of 77 submissions. This volume offers a wide range to following subjects on theoretical and practical aspects of big data analytics and knowledge discovery as a new generation of big data repository, data pre-processing, data mining, text mining, sequences, graph mining, and parallel processing. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Big Data Analytics and Knowledge Discovery / Golfarelli, Matteo ; Wrembel, Robert ; Kotsis, Gabriele ; Tjoa, A Min ; Khalil, Ismail
TÃtulo : Big Data Analytics and Knowledge Discovery : 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. Idioma : Inglés (eng) 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 Clasificación: 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. Tipo de medio : Computadora Summary : 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. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Big Data Analytics and Knowledge Discovery : 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.
Idioma : Inglés (eng)
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 Clasificación: 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. Tipo de medio : Computadora Summary : 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. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Database and Expert Systems Applications / Hartmann, Sven ; Küng, Josef ; Chakravarthy, Sharma ; Anderst-Kotsis, Gabriele ; Tjoa, A Min ; Khalil, Ismail
TÃtulo : Database and Expert Systems Applications : 30th International Conference, DEXA 2019, Linz, Austria, August 26–29, 2019, Proceedings, Part I / Tipo de documento: documento electrónico Autores: Hartmann, Sven, ; Küng, Josef, ; Chakravarthy, Sharma, ; Anderst-Kotsis, Gabriele, ; Tjoa, A Min, ; Khalil, Ismail, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2019 Número de páginas: XXVI, 447 p. 233 ilustraciones, 111 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-27615-7 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Procesamiento de datos Gestión de base de datos Software de la aplicacion Inteligencia artificial Protección de datos MinerÃa de datos y descubrimiento de conocimientos Aplicaciones informáticas y de sistemas de información Seguridad de datos e información Clasificación: 6.312 Resumen: Este conjunto de dos volúmenes de LNCS 11706 y LNCS 11707 constituye las actas arbitradas de la 30.ª Conferencia Internacional sobre Aplicaciones de Sistemas Expertos y Bases de Datos, DEXA 2019, celebrada en Linz, Austria, en agosto de 2019. Los 32 artÃculos completos presentados junto con 34 artÃculos breves fueron cuidadosamente revisado y seleccionado entre 157 presentaciones. Los artÃculos están organizados en las siguientes secciones temáticas: Parte I: Gestión y análisis de Big Data; estructuras de datos y gestión de datos; gestión y procesamiento del conocimiento; autenticidad, privacidad, seguridad y confianza; coherencia, integridad, calidad de los datos; Sistemas de Soporte a la Decisión; minerÃa y almacenamiento de datos. Parte II: Bases de datos distribuidas, paralelas, P2P, grid y en la nube; recuperación de información; Web Semántica y ontologÃas; procesamiento de información; bases de datos temporales, espaciales y de alta dimensión; Descubrimiento del conocimiento; servicios web. Nota de contenido: Big Data Management and Analytics -- Optimization of Row Pattern Matching over Sequence Data in Spark SQL -- Rainfall Estimation from Traffic Cameras -- Towards Identifying De-Anonymisation Risks in Distributed Health Data Silos -- An Attribute-Based Fine-Grained Access Control Mechanism for HBase -- Data Structures and Data Management -- Lopper: An Efficient Method for Online Log Pattern Mining based on Hybrid Clustering Tree -- Discord Monitoring for Streaming Time-series -- Partially Indexing on Flash Memory -- HGraph: A Connected-Partition Approach to Proximity Graphs for Similarity Search -- Management and Processing of Knowledge -- Statistical Processing of Stopwords on SNS -- Multiple Choice Question Answering in the Legal Domain Using Reinforced Co-occurrence -- Probabilistic Algorithm to Predict Missing Facts from Knowledge Graphs -- Semantic Oppositeness Embedding Using an Autoencoder-based Learning Model -- COMET: A Contextualized Molecule-based Matching Technique.-Authenticity, Privacy, Security and Trust -- Differentially Private Non-parametric Machine Learning as a Service -- PURE: A Privacy Aware Rule-Based Framework over Knowledge Graphs -- FFT-2PCA: a new Feature Extraction Method for Data-Based Fault Detection -- Consistency, Integrity, Quality of Data -- ADaQL to Monitor Data Quality in Machine Learning Applications -- Automated Detection and Monitoring of Advanced Data Quality Rules -- Effect of Imprecise Data Income-flow Variability on Harvest Stability: A Quantile-based Approach -- Decision Support Systems -- Fairness-enhancing interventions in stream classification -- Early turnover prediction of new restaurant employees from their attendance records and attributes -- An Efficient Premiumness and Utility-based Itemset Placement Scheme for Retail Stores -- Data Lakes: Trends and Perspectives -- An Efficient Greedy Algorithm for Sequence Recommendation -- Discovering Diverse Popular Paths using Transactional Modeling and Patter Mining -- Data Mining and Warehousing -- Representative Sample Extraction from Web Data Streams -- LogLInc: LoG Queries of Linked open data Investigator for Cube Design -- Handling the Information Backlog for Data Warehouse Development -- Ontario: Federated Query Processing against a Semantic Data Lake -- A Model-Driven Framework for the Modeling and the Description of Data-as-a-Service to Assist Service Selection and Composition -- Named Entity Recognition in Local Intent Web Search Queries -- Database Processing-in-Memory: A Vision -- Context-Aware GANs for Image Generation from Multimodal Queries. Tipo de medio : Computadora Summary : This two volume set of LNCS 11706 and LNCS 11707 constitutes the refereed proceedings of the 30th International Conference on Database and Expert Systems Applications, DEXA 2019, held in Linz, Austria, in August 2019. The 32 full papers presented together with 34 short papers were carefully reviewed and selected from 157 submissions. The papers are organized in the following topical sections: Part I: Big data management and analytics; data structures and data management; management and processing of knowledge; authenticity, privacy, security and trust; consistency, integrity, quality of data; decision support systems; data mining and warehousing. Part II: Distributed, parallel, P2P, grid and cloud databases; information retrieval; Semantic Web and ontologies; information processing; temporal, spatial, and high dimensional databases; knowledge discovery; web services. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Database and Expert Systems Applications : 30th International Conference, DEXA 2019, Linz, Austria, August 26–29, 2019, Proceedings, Part I / [documento electrónico] / Hartmann, Sven, ; Küng, Josef, ; Chakravarthy, Sharma, ; Anderst-Kotsis, Gabriele, ; Tjoa, A Min, ; Khalil, Ismail, . - 1 ed. . - [s.l.] : Springer, 2019 . - XXVI, 447 p. 233 ilustraciones, 111 ilustraciones en color.
ISBN : 978-3-030-27615-7
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Procesamiento de datos Gestión de base de datos Software de la aplicacion Inteligencia artificial Protección de datos MinerÃa de datos y descubrimiento de conocimientos Aplicaciones informáticas y de sistemas de información Seguridad de datos e información Clasificación: 6.312 Resumen: Este conjunto de dos volúmenes de LNCS 11706 y LNCS 11707 constituye las actas arbitradas de la 30.ª Conferencia Internacional sobre Aplicaciones de Sistemas Expertos y Bases de Datos, DEXA 2019, celebrada en Linz, Austria, en agosto de 2019. Los 32 artÃculos completos presentados junto con 34 artÃculos breves fueron cuidadosamente revisado y seleccionado entre 157 presentaciones. Los artÃculos están organizados en las siguientes secciones temáticas: Parte I: Gestión y análisis de Big Data; estructuras de datos y gestión de datos; gestión y procesamiento del conocimiento; autenticidad, privacidad, seguridad y confianza; coherencia, integridad, calidad de los datos; Sistemas de Soporte a la Decisión; minerÃa y almacenamiento de datos. Parte II: Bases de datos distribuidas, paralelas, P2P, grid y en la nube; recuperación de información; Web Semántica y ontologÃas; procesamiento de información; bases de datos temporales, espaciales y de alta dimensión; Descubrimiento del conocimiento; servicios web. Nota de contenido: Big Data Management and Analytics -- Optimization of Row Pattern Matching over Sequence Data in Spark SQL -- Rainfall Estimation from Traffic Cameras -- Towards Identifying De-Anonymisation Risks in Distributed Health Data Silos -- An Attribute-Based Fine-Grained Access Control Mechanism for HBase -- Data Structures and Data Management -- Lopper: An Efficient Method for Online Log Pattern Mining based on Hybrid Clustering Tree -- Discord Monitoring for Streaming Time-series -- Partially Indexing on Flash Memory -- HGraph: A Connected-Partition Approach to Proximity Graphs for Similarity Search -- Management and Processing of Knowledge -- Statistical Processing of Stopwords on SNS -- Multiple Choice Question Answering in the Legal Domain Using Reinforced Co-occurrence -- Probabilistic Algorithm to Predict Missing Facts from Knowledge Graphs -- Semantic Oppositeness Embedding Using an Autoencoder-based Learning Model -- COMET: A Contextualized Molecule-based Matching Technique.-Authenticity, Privacy, Security and Trust -- Differentially Private Non-parametric Machine Learning as a Service -- PURE: A Privacy Aware Rule-Based Framework over Knowledge Graphs -- FFT-2PCA: a new Feature Extraction Method for Data-Based Fault Detection -- Consistency, Integrity, Quality of Data -- ADaQL to Monitor Data Quality in Machine Learning Applications -- Automated Detection and Monitoring of Advanced Data Quality Rules -- Effect of Imprecise Data Income-flow Variability on Harvest Stability: A Quantile-based Approach -- Decision Support Systems -- Fairness-enhancing interventions in stream classification -- Early turnover prediction of new restaurant employees from their attendance records and attributes -- An Efficient Premiumness and Utility-based Itemset Placement Scheme for Retail Stores -- Data Lakes: Trends and Perspectives -- An Efficient Greedy Algorithm for Sequence Recommendation -- Discovering Diverse Popular Paths using Transactional Modeling and Patter Mining -- Data Mining and Warehousing -- Representative Sample Extraction from Web Data Streams -- LogLInc: LoG Queries of Linked open data Investigator for Cube Design -- Handling the Information Backlog for Data Warehouse Development -- Ontario: Federated Query Processing against a Semantic Data Lake -- A Model-Driven Framework for the Modeling and the Description of Data-as-a-Service to Assist Service Selection and Composition -- Named Entity Recognition in Local Intent Web Search Queries -- Database Processing-in-Memory: A Vision -- Context-Aware GANs for Image Generation from Multimodal Queries. Tipo de medio : Computadora Summary : This two volume set of LNCS 11706 and LNCS 11707 constitutes the refereed proceedings of the 30th International Conference on Database and Expert Systems Applications, DEXA 2019, held in Linz, Austria, in August 2019. The 32 full papers presented together with 34 short papers were carefully reviewed and selected from 157 submissions. The papers are organized in the following topical sections: Part I: Big data management and analytics; data structures and data management; management and processing of knowledge; authenticity, privacy, security and trust; consistency, integrity, quality of data; decision support systems; data mining and warehousing. Part II: Distributed, parallel, P2P, grid and cloud databases; information retrieval; Semantic Web and ontologies; information processing; temporal, spatial, and high dimensional databases; knowledge discovery; web services. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Database and Expert Systems Applications / Hartmann, Sven ; Küng, Josef ; Chakravarthy, Sharma ; Anderst-Kotsis, Gabriele ; Tjoa, A Min ; Khalil, Ismail
TÃtulo : Database and Expert Systems Applications : 30th International Conference, DEXA 2019, Linz, Austria, August 26–29, 2019, Proceedings, Part II / Tipo de documento: documento electrónico Autores: Hartmann, Sven, ; Küng, Josef, ; Chakravarthy, Sharma, ; Anderst-Kotsis, Gabriele, ; Tjoa, A Min, ; Khalil, Ismail, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2019 Número de páginas: XIX, 469 p. 428 ilustraciones, 101 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-27618-8 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Procesamiento de datos Gestión de base de datos Software de la aplicacion Inteligencia artificial Protección de datos MinerÃa de datos y descubrimiento de conocimientos Aplicaciones informáticas y de sistemas de información Seguridad de datos e información Clasificación: 6.312 Resumen: Este conjunto de dos volúmenes de LNCS 11706 y LNCS 11707 constituye las actas arbitradas de la 30.ª Conferencia Internacional sobre Aplicaciones de Sistemas Expertos y Bases de Datos, DEXA 2019, celebrada en Linz, Austria, en agosto de 2019. Los 32 artÃculos completos presentados junto con 34 artÃculos breves fueron cuidadosamente revisado y seleccionado entre 157 presentaciones. Los artÃculos están organizados en las siguientes secciones temáticas: Parte I: Gestión y análisis de Big Data; estructuras de datos y gestión de datos; gestión y procesamiento del conocimiento; autenticidad, privacidad, seguridad y confianza; coherencia, integridad, calidad de los datos; Sistemas de Soporte a la Decisión; minerÃa y almacenamiento de datos. Parte II: Bases de datos distribuidas, paralelas, P2P, grid y en la nube; recuperación de información; Web Semántica y ontologÃas; procesamiento de información; bases de datos temporales, espaciales y de alta dimensión; Descubrimiento del conocimiento; servicios web. Nota de contenido: Distributed, Parallel, P2P, Grid and Cloud databases -- Looking into the Peak Memory Consumption of Epoch-based Reclamation in Scalable In-Memory Database Systems -- Energy Efficient Data Placement and Buffer Management for Multiple Replication -- Querying Knowledge Graphs with Natural Languages -- Explaining Query Answer Completeness and Correctness With Partition Patterns -- Information Retrieval -- Research Paper Search Using a Topic-based Boolean Query Search and a General Query-based Ranking Model -- Extractive Document Summarization using Non-negative Matrix Factorization -- Succinct BWT-based Sequence prediction -- TRR: Reducing Crowdsourcing Task Redundancy -- Software Resource Recommendation for Process Execution based on the Organization's Profile -- An Experiment to Analyze the Use of Process Modeling Guidelines to Create High-Quality Process Models -- Semantic Web and Ontologies -- Novel Node Importance Measures to Improve Keyword Search over RDF Graphs -- Querying in a Workload-aware Triplestore based on NoSQL Databases -- Reverse Partitioning for SPARQL Queries: Principles and Performance Analysis -- PFed: Recommending Plausible Federated SPARQL Queries -- Representing and Reasoning about Precise and Imprecise Time Points and Intervals in Semantic Web: Dealing with Dates and Time Clocks -- Information Processing -- Context-Aware Multi-Criteria Recommendation Based on Spectral Graph Partitioning -- SilverChunk: An Efficient In-Memory Parallel Graph Processing System -- A modular approach for efficient simple question answering over knowledge base -- Scalable Machine Learning in the R Language Using a Summarization Matrix -- ML-PipeDebugger: A Debugging Tool for Data Processing Pipelines -- Temporal, Spatial, and High Dimensional Databases -- Correlation Set Discovery on Time-series Data -- Anomaly Subsequence Detection with Dynamic Local Density for Time Series -- Trajectory Similarity Join for Spatial Temporal Database -- Knowledge Discovery -- Multiviewpoint-based Agglomerative Hierarchical Clustering -- Triplet-CSSVM: Integrating Triplet-Sampling CNN and Cost-Sensitive Classification for Imbalanced Image Detection -- Discovering Partial Periodic High Utility Itemsets in Temporal Databases -- Using Mandatory Concepts for Knowledge Discovery and Data Structuring -- Topological Data Analysis with \epsilon-net Induced Lazy Witness Complex -- Analyzing Sequence Pattern Variants in Sequential Pattern Mining and its Application to Electronic Medical Record Systems -- Web Services -- Composing Distributed Data-intensive Web services using Distance-guided Memetic Algorithm -- Keyword Search based Mashup Construction with Guaranteed Diversity -- Using EDA-Based Local Search to improve the performance of NSGA-II for Multiobjective Semantic Web Service Composition -- Adaptive Caching for Data-Intensive Scientific Workflows in the Cloud. Tipo de medio : Computadora Summary : This two volume set of LNCS 11706 and LNCS 11707 constitutes the refereed proceedings of the 30th International Conference on Database and Expert Systems Applications, DEXA 2019, held in Linz, Austria, in August 2019. The 32 full papers presented together with 34 short papers were carefully reviewed and selected from 157 submissions. The papers are organized in the following topical sections: Part I: Big data management and analytics; data structures and data management; management and processing of knowledge; authenticity, privacy, security and trust; consistency, integrity, quality of data; decision support systems; data mining and warehousing. Part II: Distributed, parallel, P2P, grid and cloud databases; information retrieval; Semantic Web and ontologies; information processing; temporal, spatial, and high dimensional databases; knowledge discovery; web services. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Database and Expert Systems Applications : 30th International Conference, DEXA 2019, Linz, Austria, August 26–29, 2019, Proceedings, Part II / [documento electrónico] / Hartmann, Sven, ; Küng, Josef, ; Chakravarthy, Sharma, ; Anderst-Kotsis, Gabriele, ; Tjoa, A Min, ; Khalil, Ismail, . - 1 ed. . - [s.l.] : Springer, 2019 . - XIX, 469 p. 428 ilustraciones, 101 ilustraciones en color.
ISBN : 978-3-030-27618-8
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Procesamiento de datos Gestión de base de datos Software de la aplicacion Inteligencia artificial Protección de datos MinerÃa de datos y descubrimiento de conocimientos Aplicaciones informáticas y de sistemas de información Seguridad de datos e información Clasificación: 6.312 Resumen: Este conjunto de dos volúmenes de LNCS 11706 y LNCS 11707 constituye las actas arbitradas de la 30.ª Conferencia Internacional sobre Aplicaciones de Sistemas Expertos y Bases de Datos, DEXA 2019, celebrada en Linz, Austria, en agosto de 2019. Los 32 artÃculos completos presentados junto con 34 artÃculos breves fueron cuidadosamente revisado y seleccionado entre 157 presentaciones. Los artÃculos están organizados en las siguientes secciones temáticas: Parte I: Gestión y análisis de Big Data; estructuras de datos y gestión de datos; gestión y procesamiento del conocimiento; autenticidad, privacidad, seguridad y confianza; coherencia, integridad, calidad de los datos; Sistemas de Soporte a la Decisión; minerÃa y almacenamiento de datos. Parte II: Bases de datos distribuidas, paralelas, P2P, grid y en la nube; recuperación de información; Web Semántica y ontologÃas; procesamiento de información; bases de datos temporales, espaciales y de alta dimensión; Descubrimiento del conocimiento; servicios web. Nota de contenido: Distributed, Parallel, P2P, Grid and Cloud databases -- Looking into the Peak Memory Consumption of Epoch-based Reclamation in Scalable In-Memory Database Systems -- Energy Efficient Data Placement and Buffer Management for Multiple Replication -- Querying Knowledge Graphs with Natural Languages -- Explaining Query Answer Completeness and Correctness With Partition Patterns -- Information Retrieval -- Research Paper Search Using a Topic-based Boolean Query Search and a General Query-based Ranking Model -- Extractive Document Summarization using Non-negative Matrix Factorization -- Succinct BWT-based Sequence prediction -- TRR: Reducing Crowdsourcing Task Redundancy -- Software Resource Recommendation for Process Execution based on the Organization's Profile -- An Experiment to Analyze the Use of Process Modeling Guidelines to Create High-Quality Process Models -- Semantic Web and Ontologies -- Novel Node Importance Measures to Improve Keyword Search over RDF Graphs -- Querying in a Workload-aware Triplestore based on NoSQL Databases -- Reverse Partitioning for SPARQL Queries: Principles and Performance Analysis -- PFed: Recommending Plausible Federated SPARQL Queries -- Representing and Reasoning about Precise and Imprecise Time Points and Intervals in Semantic Web: Dealing with Dates and Time Clocks -- Information Processing -- Context-Aware Multi-Criteria Recommendation Based on Spectral Graph Partitioning -- SilverChunk: An Efficient In-Memory Parallel Graph Processing System -- A modular approach for efficient simple question answering over knowledge base -- Scalable Machine Learning in the R Language Using a Summarization Matrix -- ML-PipeDebugger: A Debugging Tool for Data Processing Pipelines -- Temporal, Spatial, and High Dimensional Databases -- Correlation Set Discovery on Time-series Data -- Anomaly Subsequence Detection with Dynamic Local Density for Time Series -- Trajectory Similarity Join for Spatial Temporal Database -- Knowledge Discovery -- Multiviewpoint-based Agglomerative Hierarchical Clustering -- Triplet-CSSVM: Integrating Triplet-Sampling CNN and Cost-Sensitive Classification for Imbalanced Image Detection -- Discovering Partial Periodic High Utility Itemsets in Temporal Databases -- Using Mandatory Concepts for Knowledge Discovery and Data Structuring -- Topological Data Analysis with \epsilon-net Induced Lazy Witness Complex -- Analyzing Sequence Pattern Variants in Sequential Pattern Mining and its Application to Electronic Medical Record Systems -- Web Services -- Composing Distributed Data-intensive Web services using Distance-guided Memetic Algorithm -- Keyword Search based Mashup Construction with Guaranteed Diversity -- Using EDA-Based Local Search to improve the performance of NSGA-II for Multiobjective Semantic Web Service Composition -- Adaptive Caching for Data-Intensive Scientific Workflows in the Cloud. Tipo de medio : Computadora Summary : This two volume set of LNCS 11706 and LNCS 11707 constitutes the refereed proceedings of the 30th International Conference on Database and Expert Systems Applications, DEXA 2019, held in Linz, Austria, in August 2019. The 32 full papers presented together with 34 short papers were carefully reviewed and selected from 157 submissions. The papers are organized in the following topical sections: Part I: Big data management and analytics; data structures and data management; management and processing of knowledge; authenticity, privacy, security and trust; consistency, integrity, quality of data; decision support systems; data mining and warehousing. Part II: Distributed, parallel, P2P, grid and cloud databases; information retrieval; Semantic Web and ontologies; information processing; temporal, spatial, and high dimensional databases; knowledge discovery; web services. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Database and Expert Systems Applications / Hartmann, Sven ; Küng, Josef ; Kotsis, Gabriele ; Tjoa, A Min ; Khalil, Ismail
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