Search Results for author:
Found 11 papers, 0 papers with code
Enhancing Textbook Question Answering Task with Large Language Models and Retrieval Augmented Generation
Textbook question answering (TQA) is a challenging task in artificial intelligence due to the complex nature of context and multimodal data.
Arabic Tweet Act: A Weighted Ensemble Pre-Trained Transformer Model for Classifying Arabic Speech Acts on Twitter
We proposed a BERT based weighted ensemble learning approach to integrate the advantages of various BERT models in dialectal Arabic speech acts classification.
Detecting Suicidality in Arabic Tweets Using Machine Learning and Deep Learning Techniques
To investigate the ability to detect suicidal thoughts in Arabic tweets automatically, we developed a novel Arabic suicidal tweets dataset, examined several machine learning models, including Na\"ive Bayes, Support Vector Machine, K-Nearest Neighbor, Random Forest, and XGBoost, trained on word frequency and word embedding features, and investigated the ability of pre-trained deep learning models, AraBert, AraELECTRA, and AraGPT2, to identify suicidal thoughts in Arabic tweets.
ALJP: An Arabic Legal Judgment Prediction in Personal Status Cases Using Machine Learning Models
In this paper, we develop a system that utilizes deep learning (DL) and natural language processing (NLP) techniques to predict the judgment outcome from Arabic case scripts, especially in cases of custody and annulment of marriage.
Hybrid Classifiers for Spatio-temporal Real-time Abnormal Behaviors Detection, Tracking, and Recognition in Massive Hajj Crowds
In large-scale crowds, we fine-tune the ResNet-50 model using YOLOv2 object detection technique to detect individuals with abnormal behaviors in the spatial domain.
Suicidal Ideation Detection on Social Media: A Review of Machine Learning Methods
Therefore, using social media to detect and identify suicidal ideation will help provide proper intervention that will eventually dissuade others from self-harming and committing suicide and prevent the spread of suicidal ideations on social media.
Pre-trained Transformer-Based Approach for Arabic Question Answering : A Comparative Study
Question answering(QA) is one of the most challenging yet widely investigated problems in Natural Language Processing (NLP).
Detection of Hate Speech using BERT and Hate Speech Word Embedding with Deep Model
The enormous amount of data being generated on the web and social media has increased the demand for detecting online hate speech.
Semi-Supervised Affective Meaning Lexicon Expansion Using Semantic and Distributed Word Representations
In this paper, we propose an extension to graph-based sentiment lexicon induction methods by incorporating distributed and semantic word representations in building the similarity graph to expand a three-dimensional sentiment lexicon.
Affect Control Processes: Intelligent Affective Interaction using a Partially Observable Markov Decision Process
In this paper, we present a probabilistic and decision-theoretic generalisation of this principle, and we demonstrate how it can be leveraged to build affectively intelligent artificial agents.
