UID:
almahu_9949139202402882
Umfang:
XXVI, 498 p. 221 illus., 161 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2021.
ISBN:
9783030858964
Serie:
Information Systems and Applications, incl. Internet/Web, and HCI ; 12858
Inhalt:
This two-volume set, LNCS 12858 and 12859, constitutes the thoroughly refereed proceedings of the 5th International Joint Conference, APWeb-WAIM 2021, held in Guangzhou, China, in August 2021. The 44 full papers presented together with 24 short papers, and 6 demonstration papers were carefully reviewed and selected from 184 submissions. The papers are organized around the following topics: Graph Mining; Data Mining; Data Management; Topic Model and Language Model Learning; Text Analysis; Text Classification; Machine Learning; Knowledge Graph; Emerging Data Processing Techniques; Information Extraction and Retrieval; Recommender System; Spatial and Spatio-Temporal Databases; and Demo.
Anmerkung:
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 Performance Evaluation -- 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.-.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783030858957
Weitere Ausg.:
Printed edition: ISBN 9783030858971
Sprache:
Englisch
DOI:
10.1007/978-3-030-85896-4
URL:
https://doi.org/10.1007/978-3-030-85896-4
