| TÃtulo : |
24th International Conference, DASFAA 2019, Chiang Mai, Thailand, April 22–25, 2019, Proceedings, Part I |
| Tipo de documento: |
documento electrónico |
| Autores: |
Li, Guoliang, ; Yang, Jun, ; Gama, João, ; Natwichai, Juggapong, ; Tong, Yongxin, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2019 |
| Número de páginas: |
XXIV, 817 p. |
| ISBN/ISSN/DL: |
978-3-030-18576-3 |
| 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 Procesamiento de datos Sistemas de almacenamiento y recuperación de información Inteligencia artificial Ciencias sociales Red de computadoras MinerÃa de datos y descubrimiento de conocimientos Almacenamiento y recuperación de información Aplicación informática en ciencias sociales y del comportamiento Redes de comunicación informática |
| Ãndice Dewey: |
005.74 Ciencia de los computadores (Archivos de datos y bases de datos) |
| Resumen: |
Este conjunto de dos volúmenes LNCS 11446 y LNCS 11447 constituye las actas arbitradas de la 24.ª Conferencia internacional sobre sistemas de bases de datos para aplicaciones avanzadas, DASFAA 2019, celebrada en Chiang Mai, Tailandia, en abril de 2019. Los 92 artÃculos completos y los 64 artÃculos breves se seleccionaron cuidadosamente de un total de 501 presentaciones. Además, se incluyen 13 artÃculos de demostración y 6 artÃculos tutoriales. Los artÃculos completos están organizados en los siguientes temas: big data; agrupamiento y clasificación; crowdsourcing; integración de datos; incrustación; gráficos; gráfico de conocimiento; aprendizaje automático; privacidad y gráfico; recomendación; red social; espacial; y espacio-temporal. Los artÃculos breves, los artÃculos de demostración y los artÃculos tutoriales se pueden encontrar en el volumen LNCS 11448, que también incluye los talleres de DASFAA 2019. |
| Nota de contenido: |
Big Data -- Accelerating Real-time Tracking Applications over Big Data Stream with Constrained Space -- A Frequency Scaling based Performance Indicator Framework for Big Data Systems -- A Time-Series Sockpuppet Detection Method for Dynamic Social Relationships -- Accelerating Hybrid Transactional/Analytical Processing using Consistent Dual-Snapshot -- HSDS: an Abstractive Model for Automatic Survey Generation -- PU-Shapelets: Towards Pattern-based Positive Unlabeled Classification of Time Series -- Clustering and Classification -- Discovering Relationship Patterns among Associated Temporal Event Sequences -- Efficient Mining of Event Periodicity in Data Series -- EPPADS: An Enhanced Phase-based Performance-Aware Dynamic Scheduler for High Job Execution Performance in Large Scale Data Clusters -- Incremental Discovery of Order Dependencies on Tuple Insertions -- Multi-view Spectral Clustering via Weighted-view Consensus Similarity and Matrix-decomposition based Discretization.-SIRCS: Slope-intercept-residual Compression by Correlation Sequencing for Multi-stream High Variation Data -- Crowdsourcing -- Fast Quorum-based Log Replication and Replay for Fast Databases -- PDCS: A Privacy-preserving Distinct Counting Scheme for Mobile Sensing -- Reinforced Reliable Worker Selection for Spatial Crowdsensing Networks -- SeqST-ResNet: A Sequential Spatial Temporal ResNet for Task Prediction in Spatial Crowdsourcing -- Towards Robust Arbitrarily Oriented Subspace Clustering -- Truthful Crowdsensed Data Trading Based on Reverse Auction and Blockchain -- Data Integration -- Selective Matrix Factorization for Multi-Relational Data Fusion -- Selectivity Estimation on Set Containment Search -- Typicality-based Across-time Mapping of Entity Sets in Document Archives -- Unsupervised Entity Alignment using Attribute Triples and Relation Triples -- Combining Meta-Graph and Attention for Recommendation over Heterogeneous Information Network -- Efficient Search of the Most Cohesive Co-Located Community in Attributed Networks -- Embedding -- A Weighted Word Embedding Model for Text Classification -- Bipartite Network Embedding via Effective Integration of Explicit and Implicit Relations -- Enhancing Network Embedding with Implicit Clustering -- MDAL: Multi-task Dual Attention LSTM Model for Semi-supervised Network Embedding -- Net2Text: An Edge Labelling Language Model for Personalized Comment Generation -- Understanding Information Diffusion via Heterogeneous Information Network Embeddings -- Graphs -- Distributed Parallel Structural Hole Detection on Big Graphs -- DynGraphGAN: Dynamic Graph Embedding via Generative Adversarial Networks -- Evaluating Mixed Patterns on Large Data Graphs Using Bitmap Views -- Heterogeneous Information Network Hashing for Fast Nearest Neighbor Search -- Learning Fine-grained Patient Similarity with Dynamic Bayesian Network Embedded RNNs -- Towards Efficient k-TriPeak Decomposition on Large Graphs -- Knowledge Graph -- Evaluating the Choice of Tags in CQA Sites -- Fast Maximal Clique Enumeration for Real-world Graphs -- Leveraging Knowledge Graph Embeddings for Natural Language Question Answering -- Measuring Semantic Relatedness with Knowledge Association Network -- SINE: Side Information Network Embedding -- A Knowledge Graph Enhanced Topic Modeling Approach for Herb Recommendation -- Knowledge Base Error Detection with Relation Sensitive Embedding -- Leon: A Distributed RDF Engine for Multi-query Processing -- MathGraph: A knowledge graph for solving mathematical exercises -- Multi-Hop Path Queries over Knowledge Graphs with Neural Memory Networks -- Sentiment Classification by Leveraging the Shared Knowledge. |
| 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 |
24th International Conference, DASFAA 2019, Chiang Mai, Thailand, April 22–25, 2019, Proceedings, Part I [documento electrónico] / Li, Guoliang, ; Yang, Jun, ; Gama, João, ; Natwichai, Juggapong, ; Tong, Yongxin, . - 1 ed. . - [s.l.] : Springer, 2019 . - XXIV, 817 p. ISBN : 978-3-030-18576-3 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 Procesamiento de datos Sistemas de almacenamiento y recuperación de información Inteligencia artificial Ciencias sociales Red de computadoras MinerÃa de datos y descubrimiento de conocimientos Almacenamiento y recuperación de información Aplicación informática en ciencias sociales y del comportamiento Redes de comunicación informática |
| Ãndice Dewey: |
005.74 Ciencia de los computadores (Archivos de datos y bases de datos) |
| Resumen: |
Este conjunto de dos volúmenes LNCS 11446 y LNCS 11447 constituye las actas arbitradas de la 24.ª Conferencia internacional sobre sistemas de bases de datos para aplicaciones avanzadas, DASFAA 2019, celebrada en Chiang Mai, Tailandia, en abril de 2019. Los 92 artÃculos completos y los 64 artÃculos breves se seleccionaron cuidadosamente de un total de 501 presentaciones. Además, se incluyen 13 artÃculos de demostración y 6 artÃculos tutoriales. Los artÃculos completos están organizados en los siguientes temas: big data; agrupamiento y clasificación; crowdsourcing; integración de datos; incrustación; gráficos; gráfico de conocimiento; aprendizaje automático; privacidad y gráfico; recomendación; red social; espacial; y espacio-temporal. Los artÃculos breves, los artÃculos de demostración y los artÃculos tutoriales se pueden encontrar en el volumen LNCS 11448, que también incluye los talleres de DASFAA 2019. |
| Nota de contenido: |
Big Data -- Accelerating Real-time Tracking Applications over Big Data Stream with Constrained Space -- A Frequency Scaling based Performance Indicator Framework for Big Data Systems -- A Time-Series Sockpuppet Detection Method for Dynamic Social Relationships -- Accelerating Hybrid Transactional/Analytical Processing using Consistent Dual-Snapshot -- HSDS: an Abstractive Model for Automatic Survey Generation -- PU-Shapelets: Towards Pattern-based Positive Unlabeled Classification of Time Series -- Clustering and Classification -- Discovering Relationship Patterns among Associated Temporal Event Sequences -- Efficient Mining of Event Periodicity in Data Series -- EPPADS: An Enhanced Phase-based Performance-Aware Dynamic Scheduler for High Job Execution Performance in Large Scale Data Clusters -- Incremental Discovery of Order Dependencies on Tuple Insertions -- Multi-view Spectral Clustering via Weighted-view Consensus Similarity and Matrix-decomposition based Discretization.-SIRCS: Slope-intercept-residual Compression by Correlation Sequencing for Multi-stream High Variation Data -- Crowdsourcing -- Fast Quorum-based Log Replication and Replay for Fast Databases -- PDCS: A Privacy-preserving Distinct Counting Scheme for Mobile Sensing -- Reinforced Reliable Worker Selection for Spatial Crowdsensing Networks -- SeqST-ResNet: A Sequential Spatial Temporal ResNet for Task Prediction in Spatial Crowdsourcing -- Towards Robust Arbitrarily Oriented Subspace Clustering -- Truthful Crowdsensed Data Trading Based on Reverse Auction and Blockchain -- Data Integration -- Selective Matrix Factorization for Multi-Relational Data Fusion -- Selectivity Estimation on Set Containment Search -- Typicality-based Across-time Mapping of Entity Sets in Document Archives -- Unsupervised Entity Alignment using Attribute Triples and Relation Triples -- Combining Meta-Graph and Attention for Recommendation over Heterogeneous Information Network -- Efficient Search of the Most Cohesive Co-Located Community in Attributed Networks -- Embedding -- A Weighted Word Embedding Model for Text Classification -- Bipartite Network Embedding via Effective Integration of Explicit and Implicit Relations -- Enhancing Network Embedding with Implicit Clustering -- MDAL: Multi-task Dual Attention LSTM Model for Semi-supervised Network Embedding -- Net2Text: An Edge Labelling Language Model for Personalized Comment Generation -- Understanding Information Diffusion via Heterogeneous Information Network Embeddings -- Graphs -- Distributed Parallel Structural Hole Detection on Big Graphs -- DynGraphGAN: Dynamic Graph Embedding via Generative Adversarial Networks -- Evaluating Mixed Patterns on Large Data Graphs Using Bitmap Views -- Heterogeneous Information Network Hashing for Fast Nearest Neighbor Search -- Learning Fine-grained Patient Similarity with Dynamic Bayesian Network Embedded RNNs -- Towards Efficient k-TriPeak Decomposition on Large Graphs -- Knowledge Graph -- Evaluating the Choice of Tags in CQA Sites -- Fast Maximal Clique Enumeration for Real-world Graphs -- Leveraging Knowledge Graph Embeddings for Natural Language Question Answering -- Measuring Semantic Relatedness with Knowledge Association Network -- SINE: Side Information Network Embedding -- A Knowledge Graph Enhanced Topic Modeling Approach for Herb Recommendation -- Knowledge Base Error Detection with Relation Sensitive Embedding -- Leon: A Distributed RDF Engine for Multi-query Processing -- MathGraph: A knowledge graph for solving mathematical exercises -- Multi-Hop Path Queries over Knowledge Graphs with Neural Memory Networks -- Sentiment Classification by Leveraging the Shared Knowledge. |
| 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 |
|  |
24th International Conference, DASFAA 2019, Chiang Mai, Thailand, April 22–25, 2019, Proceedings, Part I
