Web Information Systems Engineering – WISE 2023
Springer Verlag, Singapore
978-981-99-7253-1 (ISBN)
The 33 full and 40 short papers were carefully reviewed and selected from 137 submissions. They were organized in topical sections as follows: text and sentiment analysis; question answering and information retrieval; social media and news analysis; security and privacy; web technologies; graph embeddings and link predictions; predictive analysis and machine learning; recommendation systems; natural language processing (NLP) and databases; data analysis and optimization; anomaly and threat detection; streaming data; miscellaneous; explainability and scalability in AI.
Text and Sentiment Analysis.- Ensemble Learning Model for Medical Text Classification.- Fuzzy Based Text Quality Assessment for Sentiment Analysis.- Prompt-Learning for Semi-Supervised Text Classification.- Label-Dependent Hypergraph Neural Network for Enhanced Multi-label Text Classification.- Fast Text Comparison Based on ElasticSearch and Dynamic Programming.- Question Answering and Information Retrieval.- User Context-aware Attention Networks for Answer Selection.- Towards Robust Token Embeddings for Extractive Question Answering.- Math Information Retrieval with Contrastive Learning of Formula Embeddings.- Social Media and News Analysis.- Influence Embedding from Incomplete Observations in Sina Weibo.- Dissemination of Fact-checked News does not Combat False News: Empirical Analysis.- Highly Applicable Linear Event Detection Algorithm on Social Media with Graph Stream.- Leveraging Social Networks for Mergers and Acquisitions Forecasting.- Enhancing Trust Prediction in Attributed Social Networks with Self-Supervised Learning.- Security and Privacy.- Bilateral Insider Threat Detection: Harnessing Standalone and Sequential Activities with Recurrent Neural Networks.- ATDG: An Automatic Cyber Threat Intelligence Extraction Model of DPCNN and BIGRU Combined with Attention Mechanism.- Blockchain-Empowered Resource Allocation and Data Security for Efficient Vehicle Edge Computing.- Priv-S: Privacy-Sensitive Data Identification in Online Social Networks.- TLEF: Two-Layer Evolutionary Framework for t-closeness Anonymization.- A Dual-Layer Privacy-Preserving Federated Learning Framework.- A Privacy-Preserving Evolutionary Computation Framework for Feature Selection.- Local Difference-based Federated Learning Against Preference Profiling Attacks.- Proximity-based MAENS: A Computational Intelligence Method for Privacy-Preserving Multiple Traveling Salesmen Problem.- Empowering Vulnerability Prioritization: A Heterogeneous Graph-Driven Framework for Exploitability Prediction.- ICAD: An Intelligent Framework for Real-Time Criminal Analytics and Detection.- Web Technologies.- Web Page Segmentation: A DOM-structural Cohesion Analysis Approach.- Learning to Select the Relevant History Turns in Conversational Question Answering.- A Methodological Approach for Data-intensive Web Application Design on top of Data Lakes.- ESPRESSO: A Framework for Empowering Search on Decentralized Web.- Primary Building Blocks for Web Automation.- A Web Service Oriented Integration Solution for Capital Facilities Information Handover.- Deep Neural Network based approach for IoT service QoS prediction.- Graph Embeddings and Link Predictions.- Path-KGE: Preference-aware Knowledge Graph Embedding with Path Semantics for Link Prediction.- Efficient Graph Embedding Method for Link Prediction via Incorporating Graph Structure and Node Attributes.- Link Prediction for Opportunistic Networks Based on Hybrid Similarity Metrics and E-LSTM-D Models.- FastAGEDs: Fast Approximate Graph Entity Dependency Discovery.- Topological Network Field Preservation For Heterogeneous Graph Embedding.- Predictive Analysis and Machine Learning.- Federated Learning Performance on Early ICU Mortality Prediction with Extreme Data Distributions.- TSEGformer:Time-Space dimension dependency transformer for use in multivariate time series prediction.- Fraudulent Jobs Prediction Using Natural Language Processing and Deep Learning Sequential Models.- Prediction of Student Performance with Machine Learning Algorithms Based on ensemble learning methods.- Recommendation Systems.- Counterfactual Explanations for Sequential Recommendation with Temporal Dependencies.- Incorporating Social-aware User Preference for Video Recommendation.- Noise-augmented Contrastive Learning for Sequential Recommendation.- Self-Attention Convolutional Neural Network for Sequential Recommendation.- Informative Anchor-enhanced Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation.- Leveraging Sequential Episode Mining for Session-based News Recommendation.- Improving Conversational Recommender Systems via Knowledge enhanced Temporal Embedding.- Natural Language Processing (NLP) and Databases .- Multi-level Correlation Matching for Legal Text Similarity Modeling with Multiple Examples.- GAN-IE: Enhancing Information Extraction Through Generative Adversarial Networks with Limited Annotated Data.- An Integrated Interactive Framework for Natural Language to SQL Translation.- Task-driven Neural Natural Language Interface to Database.- Identification and Generation of Actions using Pre-trained Language Models.- GADESQL: Graph Attention Diffusion Enhanced Text-To-SQL with Single and Multi-hop Relations.- An Ensemble-based Approach for Generative Language Model Attribution.- Knowledge-grounded Dialogue Generation with Contrastive Knowledge Selection.- Data Analysis and Optimization.- A data-driven Approach to Finding K for K Nearest Neighbor Matching in Average Causal Effect Estimation.- Processing Reverse Nearest Neighbor Queries Based on Unbalanced Multiway Region Tree Index.- Solving Injection Molding Production Cost Problem Based on Combined Group Role Assignment with Costs.- CREAM: Named Entity Recognition with Concise Query and Region-Aware Minimization.- Anomaly and Threat Detection.- An Effective Dynamic Cost-Sensitive Weighting based Anomaly Multi-Classification Model for Imbalanced Multivariate Time Series.- Multivariate Time Series Anomaly Detection Based on Graph Neural Network for Big Data Scheduling System.- Study on Credit Risk Control By Variational Inference.- Streaming Data.- An Adaptive Drilling Sampling Method and Evaluation Model for Large Scale Streaming Data.- Unsupervised Representation Learning with Semantic of Streaming Time Series.- Miscellaneous.- Capo: Calibrating Device-to-Device Positioning With a Collaborative Network.- The Impact on Employability by COVID-19 Pandemic - AI case studies.- A semi-automatic framework towards building Electricity Grid Infrastructure Management ontology: A case study and retrospective.- Word-Graph2vec: An efficient word embedding approach on word co-occurrence graph using random walk technique.- Meta-Learning for Estimating Multiple Treatment Effects with Imbalance.- SML: Semantic Machine Learning Model Ontology.- Explainability and Scalability in AI.- A Comprehensive Survey of Explainable Artificial Intelligence (XAI) Methods: Exploring Transparency and Interpretability.- Scaling Machine Learning with an efficient Hybrid Distributed Framework.- Domain Adaptation with Sample Relation Reinforcement.
| Erscheinungsdatum | 24.10.2023 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | 237 Illustrations, color; 61 Illustrations, black and white; XX, 956 p. 298 illus., 237 illus. in color. |
| Verlagsort | Singapore |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Office Programme ► Outlook |
| Sozialwissenschaften | |
| Schlagworte | Artificial Intelligence • Communication Systems • Computer Networks • Computer systems • Databases • Data Mining • Education • Engineering • Information Retrieval • machine learning • Mathematics • Network Protocols • Signal Processing • Social Networks • Telecommunication networks • Telecommunication Systems • wireless telecommunication systems |
| ISBN-10 | 981-99-7253-1 / 9819972531 |
| ISBN-13 | 978-981-99-7253-1 / 9789819972531 |
| Zustand | Neuware |
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