| TÃtulo : |
5th International Joint Conference, APWeb-WAIM 2021, Guangzhou, China, August 23–25, 2021, Proceedings, Part I |
| Tipo de documento: |
documento electrónico |
| Autores: |
U, Leong Hou, ; Spaniol, Marc, ; Sakurai, Yasushi, ; Chen, Junying, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2021 |
| Número de páginas: |
XXVI, 498 p. 223 ilustraciones, 162 ilustraciones en color. |
| ISBN/ISSN/DL: |
978-3-030-85896-4 |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Palabras clave: |
Sistemas de almacenamiento y recuperación de información Software de la aplicacion Red de computadoras Almacenamiento y recuperación de información Aplicaciones informáticas y de sistemas de información Redes de comunicación informática |
| Ãndice Dewey: |
025.04 Sistemas de almacenamiento y recuperación de información |
| Resumen: |
Este conjunto de dos volúmenes, LNCS 12858 y 12859, constituye las actas minuciosamente arbitradas de la Quinta Conferencia Internacional Conjunta, APWeb-WAIM 2021, celebrada en Guangzhou, China, en agosto de 2021. Los 44 artÃculos completos presentados junto con 24 artÃculos breves, y Se revisaron y seleccionaron cuidadosamente 6 artÃculos de demostración entre 184 presentaciones. Los artÃculos están organizados en torno a los siguientes temas: Graph Mining; Procesamiento de datos; Gestión de datos; Aprendizaje de modelos temáticos y modelos de lenguaje; Análisis de Texto; Clasificación de Textos; Aprendizaje automático; Gráfico de conocimiento; Técnicas emergentes de procesamiento de datos; Extracción y Recuperación de Información; Sistema de recomendación; Bases de Datos Espaciales y Espacio-Temporales; y demostración. |
| Nota de contenido: |
Graph Mining -- Co-Authorship Prediction Based on Temporal Graph Attention -- Degree-specific Topology Learning for Graph Convolutional Network -- Simplifying Graph Convolutional Networks as Matrix Factorization -- RASP: Graph Alignment through Spectral Signatures -- FANE: A Fusion-based Attributed Network Embedding Framework -- Data Mining -- What Have We Learned from Open Review? -- Unsafe Driving Behavior Prediction for Electric Vehicles -- Resource Trading with Hierarchical Game for Computing-Power Network Market -- Analyze and Evaluate Database-Backed Web Applications with WTool -- Semi-supervised Variational Multi-view Anomaly Detection -- A Graph Attention Network Model for GMV Forecast on Online Shopping Festival -- Suicide Ideation Detection on Social Media during COVID-19 via Adversarial and Multi-task Learning -- Data Management -- An Efficient Bucket Logging for Persistent Memory -- Data Poisoning Attacks on Crowdsourcing Learning -- Dynamic Environment Simulation for Database PerformanceEvaluation -- LinKV: an RDMA-enabled KVS for High Performance and Strict Consistency under Skew -- Cheetah: An Adaptive User-space Cache for Non-volatile Main Memory File Systems -- Topic Model and Language Model Learning -- Chinese Word Embedding Learning with Limited Data -- Sparse Biterm Topic Model for Short Texts -- EMBERT: A Pre-trained Language Model for Chinese Medical Text Mining -- Self-Supervised Learning for Semantic Sentence Matching with Dense Transformer Inference Network -- An Explainable Evaluation of Unsupervised Transfer Learning for Parallel Sentences Mining -- Text Analysis -- Leveraging Syntactic Dependency and Lexical Similarity for Neural Relation Extraction -- A Novel Capsule Aggregation Framework for Natural Language Inference -- Learning Modality-Invariant Features by Cross-Modality Adversarial Network for Visual Question Answering -- Difficulty-controllable Visual Question Generation -- Incorporating Typological Features into Language Selection for Multilingual Neural Machine Translation -- Removing Input Confounder for Translation Quality Estimation via a Causal Motivated Method -- Text Classification -- Learning Refined Features for Open-World Text Classification -- Emotion Classification of Text Based on BERT and Broad Learning System -- Improving Document-level Sentiment Classification with User-Product Gated Network -- Integrating RoBERTa Fine-Tuning and User Writing Styles for Authorship Attribution of Short Texts -- Dependency Graph Convolution and POS Tagging Transferring for Aspect-based Sentiment Classification -- Machine Learning -- DTWSSE: Data Augmentation with a Siamese Encoder for Time Series -- PT-LSTM: Extending LSTM for Efficient processing Time Attributes in Time Series Prediction -- Loss Attenuation for Time Series Prediction Respecting Categories of Values -- PFL-MoE: Personalized Federated Learning Based on Mixture of Experts -- A New Density Clustering Method using Mutual Nearest Neighbor.-. |
| 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 |
5th International Joint Conference, APWeb-WAIM 2021, Guangzhou, China, August 23–25, 2021, Proceedings, Part I [documento electrónico] / U, Leong Hou, ; Spaniol, Marc, ; Sakurai, Yasushi, ; Chen, Junying, . - 1 ed. . - [s.l.] : Springer, 2021 . - XXVI, 498 p. 223 ilustraciones, 162 ilustraciones en color. ISBN : 978-3-030-85896-4 Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
| Palabras clave: |
Sistemas de almacenamiento y recuperación de información Software de la aplicacion Red de computadoras Almacenamiento y recuperación de información Aplicaciones informáticas y de sistemas de información Redes de comunicación informática |
| Ãndice Dewey: |
025.04 Sistemas de almacenamiento y recuperación de información |
| Resumen: |
Este conjunto de dos volúmenes, LNCS 12858 y 12859, constituye las actas minuciosamente arbitradas de la Quinta Conferencia Internacional Conjunta, APWeb-WAIM 2021, celebrada en Guangzhou, China, en agosto de 2021. Los 44 artÃculos completos presentados junto con 24 artÃculos breves, y Se revisaron y seleccionaron cuidadosamente 6 artÃculos de demostración entre 184 presentaciones. Los artÃculos están organizados en torno a los siguientes temas: Graph Mining; Procesamiento de datos; Gestión de datos; Aprendizaje de modelos temáticos y modelos de lenguaje; Análisis de Texto; Clasificación de Textos; Aprendizaje automático; Gráfico de conocimiento; Técnicas emergentes de procesamiento de datos; Extracción y Recuperación de Información; Sistema de recomendación; Bases de Datos Espaciales y Espacio-Temporales; y demostración. |
| Nota de contenido: |
Graph Mining -- Co-Authorship Prediction Based on Temporal Graph Attention -- Degree-specific Topology Learning for Graph Convolutional Network -- Simplifying Graph Convolutional Networks as Matrix Factorization -- RASP: Graph Alignment through Spectral Signatures -- FANE: A Fusion-based Attributed Network Embedding Framework -- Data Mining -- What Have We Learned from Open Review? -- Unsafe Driving Behavior Prediction for Electric Vehicles -- Resource Trading with Hierarchical Game for Computing-Power Network Market -- Analyze and Evaluate Database-Backed Web Applications with WTool -- Semi-supervised Variational Multi-view Anomaly Detection -- A Graph Attention Network Model for GMV Forecast on Online Shopping Festival -- Suicide Ideation Detection on Social Media during COVID-19 via Adversarial and Multi-task Learning -- Data Management -- An Efficient Bucket Logging for Persistent Memory -- Data Poisoning Attacks on Crowdsourcing Learning -- Dynamic Environment Simulation for Database PerformanceEvaluation -- LinKV: an RDMA-enabled KVS for High Performance and Strict Consistency under Skew -- Cheetah: An Adaptive User-space Cache for Non-volatile Main Memory File Systems -- Topic Model and Language Model Learning -- Chinese Word Embedding Learning with Limited Data -- Sparse Biterm Topic Model for Short Texts -- EMBERT: A Pre-trained Language Model for Chinese Medical Text Mining -- Self-Supervised Learning for Semantic Sentence Matching with Dense Transformer Inference Network -- An Explainable Evaluation of Unsupervised Transfer Learning for Parallel Sentences Mining -- Text Analysis -- Leveraging Syntactic Dependency and Lexical Similarity for Neural Relation Extraction -- A Novel Capsule Aggregation Framework for Natural Language Inference -- Learning Modality-Invariant Features by Cross-Modality Adversarial Network for Visual Question Answering -- Difficulty-controllable Visual Question Generation -- Incorporating Typological Features into Language Selection for Multilingual Neural Machine Translation -- Removing Input Confounder for Translation Quality Estimation via a Causal Motivated Method -- Text Classification -- Learning Refined Features for Open-World Text Classification -- Emotion Classification of Text Based on BERT and Broad Learning System -- Improving Document-level Sentiment Classification with User-Product Gated Network -- Integrating RoBERTa Fine-Tuning and User Writing Styles for Authorship Attribution of Short Texts -- Dependency Graph Convolution and POS Tagging Transferring for Aspect-based Sentiment Classification -- Machine Learning -- DTWSSE: Data Augmentation with a Siamese Encoder for Time Series -- PT-LSTM: Extending LSTM for Efficient processing Time Attributes in Time Series Prediction -- Loss Attenuation for Time Series Prediction Respecting Categories of Values -- PFL-MoE: Personalized Federated Learning Based on Mixture of Experts -- A New Density Clustering Method using Mutual Nearest Neighbor.-. |
| 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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