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.