4 citations · 4 across the 8 of their papers we have counts for
8 papers
SCPP: A Unified Python Library for Soft Clustering
Kiyan Rezaee, Morteza Ziabakhsh, Artin Bahrampour +6
In this paper, we present SCPP (Soft Clustering Python Package), an open-source Python framework for soft clustering. SCPP establishes a canonical, scikit-learn-compatible estimato…
FOS: A Large-Scale Temporal Graph Benchmark for Scientific Interdisciplinary Link Prediction
Kiyan Rezaee, Morteza Ziabakhsh, Niloofar Nikfarjam +4
Interdisciplinary scientific breakthroughs mostly emerge unexpectedly, and forecasting the formation of novel research fields remains a major challenge. We introduce FOS (Future Of…
Extracting Overlapping Microservices from Monolithic Code via Deep Semantic Embeddings and Graph Neural Network-Based Soft Clustering
Morteza Ziabakhsh, Kiyan Rezaee, Sadegh Eskandari +2
Modern software systems are increasingly shifting from monolithic architectures to microservices to enhance scalability, maintainability, and deployment flexibility. Existing micro…
Empirical Evaluation of AI-Assisted Software Package Selection: A Knowledge Graph Approach
Siamak Farshidi, Amir Saberhabibi, Behbod Eskafi +5
Selecting third-party software packages in open-source ecosystems like Python is challenging due to the large number of alternatives and limited transparent evidence for comparison…
Online Continual Learning: A Systematic Literature Review of Approaches, Challenges, and Benchmarks
Seyed Amir Bidaki, Amir Mohammadkhah, Kiyan Rezaee +4
Online Continual Learning (OCL) is a critical area in machine learning, focusing on enabling models to adapt to evolving data streams in real-time while addressing challenges such…
Multi-Label Feature Selection Using Adaptive and Transformed Relevance
Sadegh Eskandari, Sahar Ghassabi
Multi-label learning has emerged as a crucial paradigm in data analysis, addressing scenarios where instances are associated with multiple class labels simultaneously. With the gro…
Understanding User Intent Modeling for Conversational Recommender Systems: A Systematic Literature Review
Siamak Farshidi, Kiyan Rezaee, Sara Mazaheri +5
Context: User intent modeling is a crucial process in Natural Language Processing that aims to identify the underlying purpose behind a user's request, enabling personalized respon…
Supervised Infinite Feature Selection
Sadegh Eskandari, Emre Akbas
In this paper, we present a new feature selection method that is suitable for both unsupervised and supervised problems. We build upon the recently proposed Infinite Feature Select…