Mohammad AL-Smadi

Qatar University

Great challenges arise due to the rapid growth of online data. The widespread use of online social networks (OSN) have enabled the generation of massive amounts of raw data where users post their own material. One interesting example of user generated data is their political views and opinions. The ability to crawl OSN and automatically analyze the...

With the prominent advances in Web interaction and the enormous growth in user-generated content, sentiment analysis has gained more interest in commercial and academic purposes. Recently, sentiment analysis of Arabic user-generated content is increasingly viewed as an important research field. However, the majority of available approaches target t...

This paper proposes a state-of-the-art research for aspect-based sentiment analysis of Arabic Hotels’ reviews using two implementations of long short-term memory (LSTM) neural networks. The first one is (a) a character-level bidirectional LSTM along with conditional random field classifier (Bi-LSTM-CRF) for aspect opinion target expressions (OTEs)...

The global spread of Coronavirus (COVID-19) has prompted imperative research into scalable and effective detection methods to curb its outbreak. The early diagnosis of COVID-19 patients has emerged as a pivotal strategy in mitigating the spread of the disease. Automated COVID-19 detection using Chest X-ray (CXR) imaging has significant potential fo...

The rapidly changing tertiary education landscape necessitates a curriculum that is both adaptive and resilient, particularly in the wake of disruptions like COVID-19 and breakthroughs in open AI. Recognising these challenges as opportunities, the higher education sector is reimagining its approach to course design and delivery. In response, univer...

Billions of people spend hours on social media platforms every day. While there are numerous known benefits of social media, hate speech and abusive language on social media platforms have become an increasingly serious social problem affecting individuals and societies' psychological state. Detecting and preventing hate speech and abusive language...

The wide adoption and usage of generative artificial intelligence (AI) models, particularly Chat-GPT, has sparked a surge in research exploring their potential applications in the educational landscape. This survey examines academic literature published between November, 2022, and July, 2023, specifically targeting high-impact research from Scopus-...

The incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions. Knowledge graphs (KGs) have proven utility in this arena and are rooted in a number of healthcare applications to furnish better data representation and knowledge inference. How...

Deoxyribonucleic acid (DNA) sequencing is the process of locating the sequence of the main chemical bases in the DNA. Next-generation sequencing (NGS) is the state-of-the-art DNA sequencing technique. The NGS technique advanced the biological science in analyzing human DNA due to its scalability, high throughput, and speed. Analyzing human DNA is c...

The incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions. Knowledge graphs (KGs) have proven utility in this arena and are rooted in a number of healthcare applications to furnish better data representation and knowledge inference. How...

Currently, the whole world is fighting a very dangerous and infectious disease caused by the novel coronavirus, called COVID-19. The COVID-19 started in Wuhan, China on November of 2019 and rapidly spread around the world due to its high infection rate. So far, there is no known vaccine against this disease. Therefore, early discovery of COVID-19 i...

The increasing interactive content in the Internet motivated researchers and data scientists to conduct Aspect-Based Sentiment Analysis (ABSA) research to understand the various sentiments and the different aspects of a product in a single user’s comment. Determining the various aspects along with their polarities (positive, negative, or neutral) f...

Question-answering platforms serve millions of users seeking knowledge and solutions for their daily life problems. However, many knowledge seekers are facing the challenge to find the right answer among similar answered questions and writer's responding to asked questions feel like they need to repeat answers many times for similar questions. This...

Diabetic retinopathy is an eye disease caused by high blood sugar and pressure which damages the blood vessels in the eye. Diabetic retinopathy is the root cause of more than 1% of the blindness worldwide. Early detection of this disease is crucial as it prevents it from progressing to a more severe level. However, the current machine learning-base...

Aspect-based sentiment analysis is a special type of sentiment analysis that aims to identify the discussed aspects and their sentiment polarities in a given review. In this paper, two deep learning models are proposed to address essential aspect-based sentiment analysis tasks: aspect-category identification and aspect-sentiment classification. For...

Language comprehension and commonsense knowledge validation by machines are challenging tasks that are still under researched and evaluated for Arabic text. In this paper, we present a benchmark Arabic dataset for commonsense explanation. The dataset consists of Arabic sentences that does not make sense along with three choices to select among them...

There is a growing research interest in studying word similarity. Without a doubt, two similar words in a context may be considered different in another context. Therefore, this paper investigates the effect of the context in word similarity. The SemEval-2020 workshop has provided a shared task (Task 3: Predicting the (Graded) Effect of Context in...

In this paper, we discuss our team's work on the NADI Shared Task. The task requires classifying Arabic tweets among 21 dialects. We tested out different approaches, and the best one was the simplest one. Our best submission was using Multinational Naive Bayes classifier with n-grams as features. Our best submitted score on the test phase was 17% F...

Affect detection from text has captured the attention of researchers recently. This is due to the rapid use of social media sites (e.g. Twitter, Facebook), which allows users to express their feelings, emotions, and thoughts in textual format. Analyzing emotion-rich textual data of social networks has many real-life applications. The context of an...

The commonsense understanding and validation remains a challenging task in the field of natural language understanding. Therefore, several research papers have been published that studied the capability of proposed systems to evaluate the models ability to validate commonsense in text. In this paper, we present a benchmark Arabic dataset for common...

Extracting opinion-target expression is a core subtask to perform aspect-based sentiment analysis which aims to identify the discussed aspects within a text associated with their opinion targets and classify the sentiment as positive, negative, or neutral. This paper proposes a deep learning model to tackle the opinion-target expression extraction...

This research presents our team KEIS@JUST participation at SemEval-2020 Task 12 which represents shared task on multilingual offensive language. We participated in all the provided languages for all subtasks except sub-task-A for the English language. Two main approaches have been developed the first is performed to tackle both languages Arabic and...

This paper describes the participation of the SAJA team to the TRAC 2020 shared task on aggressive identification in the English text. we have developed a system based on transfer learning technique depending on universal sentence encoder (USE) embedding that will be trained in our developed model using xgboost classifier to identify the aggressive...

Due to the growing quantity of information available on the Web, recommender systems have become crucial component for the success of online shopping stores. However, most of the existing recommender systems were only designed to improve the recommendation results and ignore the explainable recommendation aspect. Therefore, in this paper we propose...

In the digitally connected world that we are living in, people expect to get answers to their questions spontaneously. This expectation increased the burden on Question/Answer platforms such as Stack Overflow and many others. A promising solution to this problem is to detect if a question being asked is similar to a question in the database, then p...

The vast amount of unstructured data spread on a daily basis rises the need for developing effective information retrieval and extraction methods. Named Entity Recognition is a challenging classification task for structuring data into pre-defined labels, and is even more complicated when being applied on the Arabic language due to its special trait...

Opinion mining is an important step towards facilitating information in health data. Several studies have demonstrated the possibility of tracking diseases using public tweets. However, most studies were applied to English language tweets. Influenza is currently one of the world's greatest infectious disease challenges. In this study, a new approac...

Opinion mining is an important step towards facilitating information in health data. Several studies have demonstrated the possibility of tracking diseases using public tweets. However, most studies were applied to English language tweets. Influenza is currently one of the world's greatest infectious disease challenges. In this study, a new approac...

Next-Generation Sequencing (NGS) is very helpful for conducting DeoxyriboNucleic Acid (DNA) Sequencing. DNA sequencing is the process for determining the order (sequence) of the main chemical bases in the DNA. Analyzing human DNA sequencing is important for determining the possibility that a person will develop certain diseases, and/or the ability...

Social networks (SN) consist of a set of actors and connections between them. A collaboration network (ColNet) is a special type of SN, in which the actors represent researchers and the link between them indicate that they have co-authored at least one paper. ColNet analysis reveals how researchers interact and behave. A wide range of applications...

The interchangeably connected Web technologies and the advancements that accompany the semantic web content’s leaps, have raised many challenges in the results’ retrieval process especially for the Arabic Language. This research targets an important, yet insufficiently precedent, area in using Linked Open Data (LOD) for Automatic Question Answering...

Attributing a piece of text to its true author is called Authorship Authentication (AA). This work addresses the AA problem of Arabic tweets. Arabic language is both challenging and understudied. Existing approaches on authenticating Arabic tweets used bag of words features or Stylometric Features coupled with classifiers like SVM. However, the rep...

16th ACS/IEEE International Conference on Computer Systems and Applications AICCSA 2019

Scholarly peer review is a process of evaluating the suitability of a research work for publication judged by qualified researchers. A professional peer review process ensures the quality of the produced scientific research work. However, there are two main challenges to achieve professional peer review: (1) selecting reviewers with similar compete...

In the digitally connected world that we are living in, people expect to get answers to their questions spontaneously. This fact increased the burden on the Question/Answer platforms such as Stack Overflow and many others. A promising solution to this problem is to detect if a question being asked similar to a question in the database and present t...

An honest peer-review process is a key for producing high quality scientific research. However, this process depends on two main factors: (1) the expertise of reviewers in the topic of a submitted paper and (2) the relationships between reviewers and authors. To satisfy the first factor, editors and conferences chairs manually select reviewers. Whe...

Emotion Detection (ED) from text has been an active research field recently. It has attracted the attention of researchers as it can measure the emotional contexts while humans interact with computers. Humans could express their emotion in various ways; using typed text, facial expressions, speech, gestures, and physiological measures. ED is consid...

In this paper, we describe our team’s effort on the MADAR Shared Task on Arabic Fine-Grained Dialect Identification. The task requires building a system capable of differentiating between 25 different Arabic dialects in addition to MSA. Our approach is simple. After preprocessing the data, we use Data Augmentation (DA) to enlarge the training data...

Tweets provide a continuous update on daily events, however they are noisy text, personalized and challenging to be understood by machines. This shows a need for event extraction and representation approaches. This research describes a state-of-the-art supervised machine learning approach for extracting events out of Arabic tweets. The proposed app...

Named entity recognition (NER) is considered as one of the important tasks of natural languages processing (NLP). This paper presents two approaches that were developed for Arabic named entity recognition (ANER). The first approach is based on a traditional machine learning method of using the conditional random fields (CRF) trained with predefined...

Named entity recognition (NER) is considered as one of the important tasks of natural languages processing (NLP). This paper presents two approaches that were developed for Arabic named entity recognition (ANER). The first approach is based on a traditional machine learning method of using the conditional random fields (CRF) trained with predefined...

This paper reviews the research articles published in the years between 2006 and 2017 with a focus on using Linked Data technologies for enhancing learning. For this purpose, a survey was conducted and articles were selected according to two main criteria: (1) the paper must be in the technology-enhanced learning domain and published in one of the...

Next-generation smart cities and Internet of Things (IoT) are getting more mature in terms of services and infrastructure requirements. Multiple smart vehicle applications are being conceived these days, including road traffic, road safety and infotainment, all of which are suffering from the WAN-latency problem. In this paper, we propose a Vehicul...

This research proposes an enhanced approach of decoupling assessment and serious games to support fire evacuation training in smart education. The proposed assessment approach employs an evidence-based dynamic assessment and feedback to guide players through school’s building evacuation. Experimentation results show the applicability of the propose...

In Social Network Analysis (SNA), a common algorithm for community detection iteratively applies three phases: spectral mapping, clustering (using either the Fuzzy C-Means or the K-Means algorithms) and modularity computation. Despite its effectiveness, this method is not very efficient. A feasible solution to this problem is to use Graphics Proces...

This research presents an enhanced approach for Aspect-Based Sentiment Analysis (ABSA) of Hotels' Arabic reviews using supervised machine learning. The proposed approach employs a state-of-the-art research of training a set of classifiers with morphological, syntactic, and semantic features to address the research tasks namely: (a) T1:Aspect Catego...

In this research, state-of-the-art approaches based on supervised machine learning are presented to address the challenges of aspect-based sentiment analysis (ABSA) of Arabic Hotels' reviews. Two approaches of deep recurrent neural network (RNN) and support vector machine (SVM) are implemented and trained along with lexical, word, syntactic, morpho...

This paper aims at fostering the domain of Arabic affective news analysis through providing: (a) a benchmark annotated Arabic dataset of news for affective news analysis, (b) an aspect-based sentiment analysis (ABSA) approach for evaluating the sentimental affect of Arabic news posts on the reader, and (c) a baseline approach with a common evaluati...

This research proposes a framework for aspect-based sentiment analysis (ABSA) of Hotels' reviews. The proposed framework consists of: (a) a reference human annotated Arabic dataset to support ABSA tasks such as aspect category identification, opinion target expression extraction, and opinion sentiment polarity. The dataset was annotated on both sen...

Sentiment Analysis (SA) is the process of determining the sentiment of a text written in a natural language to be positive, negative or neutral. It is one of the most interesting subfields of natural language processing (NLP) and Web mining due to its diverse applications and the challenges associated with applying it on the massive amounts of text...

Social Network Analysis (SNA) has been gaining a lot of attention lately. One of the common steps in SNA is community detection. SNA literature has many interesting algorithms for community detection. One of the popular ones was proposed by Newman and it is mainly revolved around using a clustering algorithm. Three phases are iteratively applied in...

The top-to-down and bottom-to-up processes in the semantic competence management of curriculum development in higher education context were investigated based on different semantic systems for curriculum management. As a result the paper proposes the framework and the three interrelated curriculum maturing cycles of (i) standards maturing, (ii) cur...

One of the important features of Social Networks (SNs) is community structure detection. Several methods have been proposed to address this problem. One of the interesting methods is based on the famous Fuzzy C-Means (FCM) clustering algorithm. This method consists of three phases: spectral mapping, FCM clustering and modularity computation. Despit...

Tweets provide a continuous update on current events. However, Tweets are short, personalized and noisy, thus raises more challenges for event extraction and representation. Extracting events out of Arabic tweets is a new research domain where few examples – if any – of previous work can be found. This paper describes a knowledge-based approach for...

This research aims at tackling the problem of Arabic Named-Entity Disambiguation (ANED) through an enhanced approach of information extraction from Arabic Wikipedia and Linked Open Data (LOD). The approach uses query label expansion and text similarity techniques to disambiguate entities of the types: person, location, and organization. A reference...

Recently, research has become increasingly interested in developing tools that are able to automatically create test items out of text-based learning contents. Such tools might not only support instructors in creating tests or exams but also learners in self-assessing their learning progress. This paper presents an enhanced automatic question-creat...

This paper aims at fostering the domain of Arabic affective news analysis through providing: (a) a benchmark annotated Arabic dataset of news for affective news analysis, (b) an aspect-based sentiment analysis (ABSA) approach for evaluating the sentimental affect of Arabic news posts on the reader, and (c) a baseline approach with a common evaluati...

The rapid increase in digital information has raised great challenges especially when it comes to automated content analysis. The adoption of social media as a communication channel for political views demands automated methods for posts' tone analysis, sentiment analysis, and emotional affect. This paper proposes a novel approach of using aspect-b...

Authorship authentication of a certain text is concerned with correctly attributing it to its author based on its contents. It is a very important problem with deep root in history as many classical texts have doubtful attributions. The information age and ubiquitous use of the Internet is further complicating this problem and adding more dimension...

Sentiment Analysis (SA) is the process of determining the sentiment of a text written in a natural language to be positive, negative or neutral. It is one of the most interesting subfields of natural language processing (NLP) and Web mining due to its diverse applications and the challenges associated with applying it on the massive amounts of text...

With the enormous growth in the World Wide Web (WWW), billions of webpages are available online. The shift towards the so called Web of Data demands extracting relationships among named entities of web content and representing them into RDF (Resource Description Framework) graphs. A key step to foster the web of data is the disambiguation of named...

Engaging learners long enough to see them through to the end of a course has become one of the most significant problems faced by e-learning developers. The lack of engagement in e-learning can be attributed to three main issues: interaction, challenge and context. Therefore, learning types with high level of intera