Zenun Kastrati

• PhD in Computer Science
• Professor (Associate) at Linnaeus University

Large Language Models (LLMs) have revolutionized many industrial applications and paved the way for fostering a new research direction in many fields. Conventional Natural Language Processing (NLP) techniques, for instance, are no longer necessary for many text-based tasks, including polarity estimation, sentiment and emotion classification, and ha...

The exploration of automated wrist fracture recognition has gained considerable research attention in recent years. In practical medical scenarios, physicians and surgeons may lack the specialized expertise required for accurate X-ray interpretation, highlighting the need for machine vision to enhance diagnostic accuracy. However, conventional reco...

Automated wrist fracture recognition has become a crucial research area due to the challenge of accurate X-ray interpretation in clinical settings without specialized expertise. With the development of neural networks, YOLO models have been extensively applied to fracture detection recently. However, detection models can struggle when trained on sm...

The advent of deep neural networks and improved computational power have brought a revolutionary transformation in the fields of computer vision and image processing. Within the realm of computer vision, there has been a significant interest in the area of synthetic image generation, which is a creative side of AI. Many researchers have introduced...

The exploration of automated wrist fracture recognition has gained considerable research attention in recent years. In practical medical scenarios, physicians and surgeons may lack the specialized expertise required for accurate X-ray interpretation, highlighting the need for machine vision to enhance diagnostic accuracy. However, conventional reco...

Wrist pathologies, particularly fractures common among children and adolescents, present a critical diagnostic challenge. While X-ray imaging remains a prevalent diagnostic tool, the increasing misinterpretation rates highlight the need for more accurate analysis, especially considering the lack of specialized training among many surgeons and physi...

Wrist pathologies, particularly fractures common among children and adolescents, present a critical diagnostic challenge. While X-ray imaging remains a prevalent diagnostic tool, the increasing misinterpretation rates highlight the need for more accurate analysis, especially considering the lack of specialized training among many surgeons and physi...

Diagnosing and treating abnormalities in the wrist, specifically distal radius, and ulna fractures, is a crucial concern among children, adolescents, and young adults, with a higher incidence rate during puberty. However, the scarcity of radiologists and the lack of specialized training among medical professionals pose a significant risk to patient...

Diagnosing and treating abnormalities in the wrist, specifically distal radius, and ulna fractures, is a crucial concern among children, adolescents, and young adults, with a higher incidence rate during puberty. However, the scarcity of radiologists and the lack of specialized training among medical professionals pose a significant risk to patient...

Nowadays, various applications across industries, healthcare, and security have begun adopting automatic sentiment analysis and emotion detection in short texts, such as posts from social media. Twitter stands out as one of the most popular online social media platforms due to its easy, unique, and advanced accessibility using the API. On the other...

The Internet has become one of the significant sources for sharing information and expressing users’ opinions about products and their interests with the associated aspects. It is essential to learn about product reviews; however, to react to such reviews, extracting aspects of the entity to which these reviews belong is equally important. Aspect-b...

In domains such as medical and healthcare, the interpretability and explainability of machine learning and artificial intelligence systems are crucial for building trust in their results. Errors caused by these systems, such as incorrect diagnoses or treatments, can have severe and even life-threatening consequences for patients. To address this is...

The introduction of MOOCs raised the expectation of a disrupting potential within education systems. These expectations, however, have not been met, despite the fact that more than a decade has passed. The main reason seems to be the high dropout rate of students in Massive Open Online Courses (MOOCs). With the start of the COVID-19 pandemic, the c...

Low-resource languages are gaining much-needed attention with the advent of deep learning models and pre-trained word embedding. Though spoken by more than 230 million people worldwide, Urdu is one such low-resource language that has recently gained popularity online and is attracting a lot of attention and support from the research community. One...

Original synthetic content writing is one of the human abilities that algorithms aspire to emulate. The advent of sophisticated algorithms, especially based on neural networks has shown promising results in recent times. A watershed moment was witnessed when the attention mechanism was introduced which paved the way for transformers, a new exciting...

In the field of text classification, researchers have repeatedly shown the value of transformer-based models such as Bidirectional Encoder Representation from Transformers (BERT) and its variants. Nonetheless, these models are expensive in terms of memory and computational power but these models have not been utilized to classify long documents of...

The rise in technological advancements and Social Networking Sites (SNS) made people more engaged in their virtual lives. Research has revealed that people feel more comfortable posting their feelings, including suicidal thoughts, on SNS than discussing them through face-to-face settings due to the social stigma associated with mental health. This...

Recent advancements in big data, algorithms, and computing power have triggered significant enhancements in artificial intelligence (AI). Almost every aspect of travel and tourism is currently impacted by AI, which can be evidenced in a variety of applications including robots, conversational systems, smart travel agents, prediction and forecasting...

Energy prices have gone up gradually since last year, but a drastic hike has been observed recently in the past couple of months, affecting people’s thrift. This, coupled with the load shedding and energy shortages in some parts of the world, led many to show anger and bitterness on the streets and on social media. Despite subsidies offered by many...

With the rapid advancement in healthcare, there has been exponential growth in the healthcare records stored in large databases to help researchers, clinicians, and medical practitioner’s for optimal patient care, research, and trials. Since these studies and records are lengthy and time consuming for clinicians and medical practitioners, there is...

Automatic text-based sentiment analysis and emotion detection on social media platforms has gained tremendous popularity recently due to its widespread application reach, despite the unavailability of a massive amount of labeled datasets. With social media platforms in the limelight in recent years, it’s easier for people to express their opinions...

Social media was a heavily used platform by people in different countries to express their opinions about different crises, especially during the Covid-19 pandemics. This dataset is created through collecting people's comments in the news items on the official Facebook site of the National Institute of Public Health of Kosovo. The dataset contains...

Data imbalance in datasets is a common issue where the number of instances in one or more categories far exceeds the others, so is the case with the educational domain. Collecting feedback on a course on a large scale and the lack of publicly available datasets in this domain limits models’ performance, especially for deep neural network based mode...

Providing researchers and other users access to data can accelerate knowledge discovery and enhance research transparency and reliability. In this context, the FAIR vision was formulated with the goal to optimize data sharing and reuse by humans and machines. In this paper, we investigate Scandinavian open data portals using FAIR data principles. W...

In recent years, significant progress has been made in text generation. The latest text generation models are revolutionizing the domain by generating human-like text. It has gained wide popularity recently in many domains like news, social networks, movie scriptwriting, and poetry composition, to name a few. The application of text generation in v...

Many higher education institutions in the world have switched to online learning due to the ongoing COVID-19 pandemic, which also has greatly contributed towards an increase of MOOCs enrollments across various disciplines. There are many factors that can influence the learning trajectory in MOOCs settings, and in order to gain a deeper understandin...

Students’ feedback assessment became a hot topic in recent years with growing e-learning platforms coupled with an ongoing pandemic outbreak. Many higher education institutes were compelled to shift on-campus physical classes to online mode, utilizing various online teaching tools and massive open online courses (MOOCs). For many institutes, includ...

During the past two years, the entire world has been coping with the consequences of the COVID-19 pandemics. The need for physical distancing, forced an accelerated digital transformation of the education sector. The emergency remote education (ERE) has been manifested differently across diverse countries in the world. In this paper, we bring a cas...

Urdu is still considered a low-resource language despite being ranked as the world’s 10th most spoken language with nearly 230 million speakers. The scarcity of benchmark datasets in low-resource languages has led researchers to utilize more ingenious techniques to curb the issue. One such option widely adopted is to use language translation servic...

Smart home applications are ubiquitous and have gained popularity due to the overwhelming use of Internet of Things (IoT)-based technology. The revolution in technologies has made homes more convenient, efficient, and even more secure. The need for advancement in smart home technology is necessary due to the scarcity of intelligent home application...

During the pandemic, when people needed to physically distance, social media platforms have been one of the outlets where people expressed their opinions, thoughts, sentiments, and emotions regarding the pandemic situation. The core object of this research study is the sentiment analysis of peoples’ opinions expressed on Facebook regarding the curr...

It has been more than a year since the coronavirus (COVID-19) engulfed the whole world, disturbing the daily routine, bringing down the economies, and killing two million people across the globe at the time of writing. The pandemic brought the world together to a joint effort to find a cure and work toward developing a vaccine. Much to the anticipa...

In the last decade, sentiment analysis has been widely applied in many domains, including business, social networks and education. Particularly in the education domain, where dealing with and processing students’ opinions is a complicated task due to the nature of the language used by students and the large volume of information, the application of...

Nowadays, Artificial Intelligence (AI) is proving to be successful for solving complex problems in various application domains. However, despite the numerous success stories of AI-systems, one challenge that characterizes these systems is that they often lack transparency in terms of understandability and explainability. In this study, we propose t...

Data imbalance is a frequently occurring problem in classification tasks where the number of samples in one category exceeds the amount in others. Quite often, the minority class data is of great importance representing concepts of interest and is often challenging to obtain in real-life scenarios and applications. Imagine a customers’ dataset for...

How different cultures react and respond given a crisis is predominant in a society's norms and political will to combat the situation. Often, the decisions made are necessitated by events, social pressure, or the need of the hour, which may not represent the nation's will. While some are pleased with it, others might show resentment. Coronavirus (...

How different cultures react and respond given a crisis is predominant in a society's norms and political will to combat the situation. Often the decisions made are necessitated by events, social pressure, or the need of the hour, which may not represent the will of the nation. While some are pleased with it, others might show resentment. Coronavir...

Open Data are increasingly being used for innovation, developing government strategies, and enhancing the transparency of the public sector. This data is aimed to be available to all people regardless of their abilities, professions and knowledge. Research is showing, however, that open data, besides being physically inaccessible to people with spe...

Students’ feedback is an effective mechanism that provides valuable insights about teaching-learning process. Handling opinions of students expressed in reviews is a quite labour-intensive and tedious task as it is typically performed manually by the human intervention. While this task may be viable for small-scale courses that involve just a few s...

In this article, we present a dataset containing word embeddings and document topic distribution vectors generated from MOOCs video lecture transcripts. Transcripts of 12,032 video lectures from 200 courses were collected from Coursera learning platform. This large corpus of transcripts was used as input to two well-known NLP techniques, namely Wor...

The advent of MOOC platforms brought an abundance of video educational content that made the selection of best fitting content for a specific topic a lengthy process. To tackle this challenge in this paper we report our research efforts of using deep learning techniques for managing and classifying educational content for various search and retriev...

Open educational video resources are gaining popularity with a growing number of massive open online courses (MOOCs). This has created a niche for content providers to adopt effective solutions in automatically organizing and structuring of educational resources for maximum visibility. Recent advances in deep learning techniques are proving useful...

This paper presents a semantically rich document representation model for automatically classifying financial documents into predefined categories utilizing deep learning. The model architecture consists of two main modules including document representation and document classification. In the first module, a document is enriched with semantics usin...

This paper proposes to use acoustic features employing deep neural network (DNN) and convolutional neural network (CNN) models for classifying video lectures in a massive open online course (MOOC). The models exploit the voice pattern of the lecturer for identification and for classifying the video lecture according to the right speaker category. F...

Massive Open Online Courses (MOOCs) have transformed the way educational institutions deliver high-quality educational material to the onsite and distance learners across the globe. As a result, a new paradigm shifts as to how learners acquire and benefit from the wealth of knowledge provided by a MOOC at their doorstep nowadays in contrast to the...

This paper provides a comprehensive performance analysis of parametric and non-parametric machine learning classifiers including a deep feed-forward multi-layer perceptron (MLP) network on two variants of improved Concept Vector Space (iCVS) model. In the first variant, a weighting scheme enhanced with the notion of concept importance is used to as...

MOOC represents an ultimate way to deliver educational content in higher education settings by providing high-quality educational material to the students throughout the world. Considering the differences between traditional learning paradigm and MOOCs, a new research agenda focusing on predicting and explaining dropout of students and low completi...

The wide use of ontology in different applications has resulted in a plethora of automatic approaches for population and enrichment of an ontology. Ontology enrichment is an iterative process where the existing ontology is continuously updated with new concepts. A key aspect in ontology enrichment process is the concept learning approach. A learnin...

In this paper, we propose a new document classification model which utilizes background knowledge gathered by ontologies for document representation. A document is represented using a set of ontology concepts that are acquired by exact matching technique and through identification and extraction of new terms which can be semantically related to the...

Ontology-based document classification relies on background knowledge exploited by ontologies to represent documents. Background knowledge is embedded in a document using the exact matching technique. The basic idea of this technique is to map a term to a concept by searching only the concept labels that explicitly occur in a document. Searching on...

Undoubtedly, MOOCs have the potential to introduce a new wave of technological innovation in learning. In spite of the great interest among the educators and the general public MOOCs have generated, there are some challenges that MOOCs might face when it comes to examining and determining the best pedagogical approaches that MOOCs should be based o...

One of the challenges faced by today’s web is the abundance of unstructured and unorganized information available on the Internet in form of educational documents, lecture notes, presentation slides, and multimedia recordings. Accessing and retrieving the massive amount of such resources are not an easy task, especially educational resources of ped...

The ontology-based document classification approach relies on the content meanings of a given domain exploited and captured using the ontologies of this particular domain. Domain ontologies consist of a set of concepts and relations which links these concepts. However, they often do not provide an in-depth coverage of concepts thereby limiting thei...

Many online learning websites and learning management sys- tems (LMS) provide social collaboration and networking tools to aid learning and to interact with peers for knowledge sharing. The benefit of collaborating with each other is certainly undeniable, such tools, how- ever, can be a distraction from the actual tasks for learners. The paper pres...

One of the challenges faced by today’s web is the abundance of unstructured and unorganized information available on the Internet in the form of educational documents, lecture notes, presentation slides, and multimedia recordings. Accessing and retrieving the massive amount of such resources are not an easy task, especially educational resources of...

This paper presents a novel concept enrichment objective metric combining contextual and semantic information of terms extracted from the domain documents. The proposed metric is called SEMCON which stands for semantic and contextual objective metric. It employs a hybrid learning approach utilizing functionalities from statistical and linguistic on...

This paper proposes an improved concept vector space (ICVS) model which takes into account the importance of ontology concepts. Concept importance shows how important a concept is in an ontology. This is reflected by the number of relations a concept has to other concepts. Concept importance is computed automatically by converting the ontology into...

In this paper, we are proposing a new semantic and contextual based document image classification framework. The framework is composed of two main modules. The first one is the text analysis module (TAM) which processes document images and extracts words from the image, and second one is the SEMCON, which is a semantic and contextual objective metr...

Analysing users’ behaviour and social activity for investigating suspects is an area of great interest nowadays, particularly investigating the activities of users on Online Social Networks (OSNs) for crimes. The criminal activity analysis provides a useful source of information for law enforcement and intelligence agencies across the globe. Curren...

The text document classification employs either text based approach or semantic based approach to index and retrieve text documents. The former uses keywords and therefore provides limited capabilities to capture and exploit the conceptualization involved in user information needs and content meanings. The latter aims to solve these limitations usi...

Ontologies represent an efficient way of semantic web application on e-learning and offer great opportunity by bringing great advantages to e-learning systems. Nevertheless, despite the many advantages that we get from using ontologies, in terms of structuring the data, there are still many unresolved problems related to the difficulties about gett...

Domain ontologies are a good starting point to model in a formal way the basic vocabulary of a given domain. However, in order for an ontology to be usable in real applications, it has to be supplemented with lexical resources of this particular domain. The learning process of enriching domain ontologies with new lexical resources employed in the e...

This paper proposes a new objective metric called the SEMCON to enrich existing concepts in domain ontologies for describing and organizing multimedia documents. The SEMCON model exploits the document contextually and semantically. The preprocessing module collects a document and partitions that into several passages. Then a morpho-syntatic analysi...

This paper proposes an adaptive document representation (concept vector space model) using Markov Chain model. The vector space representation is one of the most common models for representing documents in classification process. The document classification based on ontology classification approach is represented as a vector, whose components are o...

This paper examines building of the course ontology for describing and organizing hyperlinked pedagogical content. The ontology is used to structure and classify multimedia learning objects (MLO) in hyperlinked pedagogical platform called HIP, and to assist students to search for lectures and other teaching materials in a reasonable time and more e...

This paper describes a new game assessment metric for the online gamer. The metric is in line with a mathematical model currently used for network planning assessment. In addition to the traditional network-based parameters such as delay, jitter and packet loss, new parameters based on subjective assessment are introduced. The metric aims to estima...