Conference: The 3rd Conference on Automated Knowledge Base Construction Authors: Chadi Helwe, Chloé Clavel, Fabian Suchanek Abstract: Recent years have seen impressive performance of transformer-based models on different natural language processing tasks. However, it is not clear to what degree the transformers can reason on natural language. To shed light on this question, this survey paper discusses the
Category: Uncategorized
A Semi-Supervised BERT Approach for Arabic Named Entity Recognition
Conference: The 5th Arabic Natural Language Workshop Authors: Chadi Helwe, Ghassan Dib, Mohsen Shamas, Shady Elbassuoni Abstract: Named entity recognition (NER) plays a significant role in many applications such as information extraction, information retrieval, question answering, and even machine translation. Most of the work on NER using deep learning was done for non-Arabic languages like English
A Deep Learning Approach to Detect the Demarcation Line in OCT Images
Conference: The 24th Conference on Medical Image Understanding and Analysis (to appear) Authors: Chadi Helwe, Shady Elbassuoni, Ahmad R. Dhaini, Lily Chacra, Shady Awwad Abstract: Corneal cross-linking (CXL) is a surgical intervention to treat the progression of an eye disease called keratoconus that may lead to significant loss of visual acuity. Manually detecting the presence
Assessing Arabic Weblog Credibility via Deep Co-learning
Conference: The 4th Arabic Natural Language Workshop Authors: Chadi Helwe, Shady Elbassuoni, Ayman Al Zaatari, Wassim El Hajj Abstract: Assessing the credibility of online content has garnered a lot of attention lately. We focus on one such type of online content, namely weblogs or blogs for short. Some recent work attempted the task of automatically
Arabic Named Entity Recognition via Deep Co-learning
Journal: Artificial Intelligence Review Authors: Chadi Helwe, Shady Elbassuoni Abstract: Named entity recognition (NER) is an important natural language processing (NLP) task with many applications. We tackle the problem of Arabic NER using deep learning based on Arabic word embeddings that capture syntactic and semantic relationships between words. Deep learning has been shown to perform
CCS Coding of Discharge Diagnoses via Deep Neural Networks
Conference: The 7th Conference on Digital Health Authors: Chadi Helwe, Shady Elbassuoni, Mirabelle Geha, Eveline Hitti, Carla Makhlouf Obermeyer Abstract: A standard procedure in the medical domain is to code discharge diagnoses into a set of manageable categories known as the CCS codes. This is typically done by first manually coding the discharge diagnoses
Methodical Evaluation of Arabic Word Embeddings
Conference: The 55th Annual Meeting of the Association for Computational Linguistics Authors: Mohammed Elrazzaz, Shady Elbassuoni, Khaled Shaban, Chadi Helwe Abstract: Many unsupervised learning techniques have been proposed to obtain meaningful representations of words from text. In this study, we evaluate these various techniques when used to generate Arabic word embeddings. We first build
Reconfigurable and Adaptive Spark Applications
Conference: The 7th International Conference on Cloud Computing and Services Science Authors: Bilal Abi Farraj, Wael Al Rahal Al Orabi, Chadi Helwe, Mohamad Jaber, Mohamad Omar Kayali, Mohamed Nassar Abstract: The contribution of this paper is two-fold. First, we propose a Domain Specific Language (DSL) to easily reconfigure and compose Spark applications. For each
About Me
Hello World !!!! My name is Chadi Helwe; I am a research assistant at the American University of Beirut working on deep learning. I graduated from the same university with an MSc in Computer Science. My master thesis was about Arabic Named Entity Recognition via Deep Co-learning. I like everything related to AI, especially machine