[J5] Trustworthiness-Driven Graph Convolutional Networks for Signed Network Embedding
[C8] Low Mileage, High Fidelity: Evaluating Hypergraph Expansion Methods by Quantifying the Information Loss
[J4] A Framework for Accurate Community Detection on Signed Networks Using Adversarial Learning
[J3] Community Reinforcement: An Effective and Efficient Preprocessing Method for Accurate Community Detection
[C7] Adversarial Learning of Balanced Triangles for Accurate Community Detection on Signed Networks
[J2] FORESEE: An Effective and Efficient Framework for Estimating the Execution Times of IO Traces on the SSD
[C6] CR-Graph: Commnuity Reinforcement for Accurate Community Detection
[C5] CR-Graph: Commnuity Reinforcement for Accurate Community Detection
[J1] The uFLIP Benchmark Revisited for Evaluating SSDs
[C4] A Methodology for Estimating Execution Times of IO Traces in SSDs
[C3] Exploiting the uFLIP Benchmark for Analyzing SSDs Performance
[C2] Running Data Mining Algorithms on SSDs
[C1] Selecting Similar Users in Collaborative Filtering
[DC12] Constructing a Graph-Based arXiv Dataset By Reflecting the Research Trend in Computer Science
[DC11] Evaluating the Performance of Hypergraph Embedding Methods According to Hypergraph Sparsity
[DJ1] CoAID+: COVID-19 News Cascade Dataset for Social Context Based Fake News Detection
[DC10] COVID-19 Cascade Dataset for Fake News Detection
[DC9] A Preprocessing Method for Accurate Link Prediction on Social Networks
[DC8] Performance Comparison of Similarity-Based Link Prediction in Social Networks
[DC7] Performance Comparison of Community Detection Algorithms in Social Networks
[DC6] A Method for Analyzing Features that Affect the Performance of SSD
[DC5] Community Detection by Sub-Community and CScan
[DC4] A Methodology for Estimating Execution Times of IO Traces on SSDs
[DC3] Anaylzing the Performance of SSDs in OLTP Environment
[DC2] Analysis on I/O Trace Replayer for SSD Performance Evaluation
[DC1] A Method for Selecting Similar Users for Collaborative Filtering