Del 14147 - Lecture Notes in Computer Science

Database and Expert Systems Applications

34th International Conference, DEXA 2023, Penang, Malaysia, August 28–30, 2023, Proceedings, Part II

Häftad, Engelska, 2023

Av Christine Strauss, Toshiyuki Amagasa, Gabriele Kotsis, A Min Tjoa, Ismail Khalil

1 869 kr

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The two-volume set, LNCS 14146 and 14147 constitutes the thoroughly refereed proceedings of the 34th International Conference on Database and Expert Systems Applications, DEXA 2023, held in Penang, Malaysia, in August 2023.The 49 full papers presented together with 35 short papers were carefully reviewed and selected from a total of 155 submissions. The papers are organized in topical sections as follows:Part I: Data modeling; database design; query optimization; knowledge representation; Part II: Rule-based systems; natural language processing; deep learning; neural networks.

Produktinformation

Utgivningsdatum2023-08-16
Mått155 x 235 x 28 mm
Vikt756 g
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor478
FörlagSpringer International Publishing AG
EAN9783031398209

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Rule-Based Systems.- RD-Classifier: Reduced Dimensionality Classifier for Alzheimer‘s Diagnosis Sup-port System.- User Interactions-aware Knowledge Graphs for Recommender Systems.- How Does the System Perceive Me? --- A Transparent and Tunable Recommender System.- MERIHARI-Area Tour Planning by Considering Regional Characteristics. -Financial Argument Quality Assessment in Earnings Conference Calls.- Explaining Decisions of Black-box Models using BARBE.- Efficient Video Captioning with Frame Similarity-based Filtering.- Trace-based Anomaly Detection with Contextual Sequential Invocations.- Fusing Fine-grained Information of Sequential News for Personalized News Recommendation.- A Finite- Domain Constraint-based Approach on the Stockyard Planning Problem.- Data Analytics Framework for Smart Waste Management Optimisation: A Key to Sustainable Future for Councils and Communities.- Natural Language Processing.- Hierarchy-aware Bilateral-Branch Network for Imbalanced Hierarchical TextClassification.- Multi-Feature and Multi-Channel GCNs for Aspect Based Sentiment Analysis.- Knowledge Injection for Aspect-Based Sentiment Classification.- Towards Ensemble-based Imbalanced Text Classification using Metric Learning.- Target and Precursor named entities recognition from scientific texts of high-temperature steel using deep neural network.- Enabling PII Discovery in Textual Data via Outlier Detection. -Deep Learning.- An Efficient Embedding Framework for Uncertain Attribute Graph.- Double-layer Attention for Long Sequence Time-Series Forecasting.- Multi-core Adaptive Merging of the Secondary Index for LSM-based Stores.- CAGAIN: Column Attention Generative Adversarial Imputation Networks.- CF-SAFF: Collaborative Filtering based on Self-Attention Mechanism and Feature Fusion.- Except-Condition Generative Adversarial Network for Generating Trajectory Data. - Next POIs Prediction for Group Recommendations: Influence-based Deep Learning Model. - Interpreting Deep Text Quantification Models.- NExtGCN: Modeling Node Importance of Graph Convolution Network by Neighbor Excitation for Recommendation.- Dual Congestion-aware Route Planning for Tourists by Multi-agent Reinforcement Learning.- Subspace Clustering Technique Using Multi-Objective Functions for Multi-class Categorical Data.- Neural Networks.- Multi-task Graph Neural Network for Optimizing the Structure Fairness.- Few-Shot Multi-Label Aspect Category Detection Utilizing Prototypical Network with Sentence-Level Weighting and Label Augmentation.- Toward Healthy Aging: Temporal Regression for Disability Prediction and Warning Decision-Making.- A Label Embedding Method via Conditional Covariance Maximization for Mul-ti-label Classification.- Integrally Private Model Selection for Deep Neural Networks.- Gaussian Process Component Mining with the Apriori Algorithm.- Learnable Filter Components For Social Recommendation.- Efficient Machine Learning-Based Prediction of CYP450 Inhibition.- A Machine-Learning Framework for Supporting Content Recommendation via User Feedback Data and Content Profiles in Content Managements Systems.- Fine-tuning Pre-Trained Model for Consumer Fraud Detection from Consumer Reviews.- Deep Multi-Interaction Hidden Interest Evolution Network for Click-through Rate Prediction.- Temporal Semantic Attention Network for Aspect-Based Sentiment Analysis.- Celestial Machine Learning from Data to Mars and Beyond with AI Feynman.