87 citations · 181 across the 11 of their papers we have counts for
12 papers
KeyKnowledgeRAG (K^2RAG): An Enhanced RAG method for improved LLM question-answering capabilities
Hruday Markondapatnaikuni, Basem Suleiman, Abdelkarim Erradi +1
Fine-tuning is an immensely resource-intensive process when retraining Large Language Models (LLMs) to incorporate a larger body of knowledge. Although many fine-tuning techniques…
SemRAG: Semantic Knowledge-Augmented RAG for Improved Question-Answering
Kezhen Zhong, Basem Suleiman, Abdelkarim Erradi +1
This paper introduces SemRAG, an enhanced Retrieval Augmented Generation (RAG) framework that efficiently integrates domain-specific knowledge using semantic chunking and knowledge…
Spatiotemporal Data Mining: A Survey on Challenges and Open Problems
Ali Hamdi, Khaled Shaban, Abdelkarim Erradi +3
Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay between space and time. Several available surveys capture STDM advances and report a wealth o…
Spatiotemporal Tensor Completion for Improved Urban Traffic Imputation
Ahmed Ben Said, Abdelkarim Erradi
Effective management of urban traffic is important for any smart city initiative. Therefore, the quality of the sensory traffic data is of paramount importance. However, like any s…
A deep-learning model for evaluating and predicting the impact of lockdown policies on COVID-19 cases
Ahmed Ben Said, Abdelkarim Erradi, Hussein Aly +1
To reduce the impact of COVID-19 pandemic most countries have implemented several counter-measures to control the virus spread including school and border closing, shutting down pu…
Predicting COVID-19 cases using Bidirectional LSTM on multivariate time series
Ahmed Ben Said, Abdelkarim Erradi, Hussein Aly +1
Background: To assist policy makers in taking adequate decisions to stop the spread of COVID-19 pandemic, accurate forecasting of the disease propagation is of paramount importance…