Blar i NTNU Open på forfatter "Kastrati, Zenun"
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Artificial Intelligence in Education: The Effectiveness of Large Language Models as Assessment Assistants
Sivakumar, Mithunan (Master thesis, 2024)Det har vært store teknologiske fremskritt innen språkbehandling (NLP) de siste årene, særlig med utviklingen av store språkmodeller (LLMer), som har vist effektiv språkforståelse. Nyere forskning har undersøkt hvordan ... -
Classifying European Court of Human Rights Cases Using Transformer-Based Techniques
Imran, Ali Shariq; Hodnefjeld, Henrik; Kastrati, Zenun; Fatima, Noureen; Daudpota, Sher Muhammad; Wani, Mudasir Ahmad (Peer reviewed; Journal article, 2023)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 ... -
Cross-Cultural Polarity and Emotion Detection Using Sentiment Analysis and Deep Learning on COVID-19 Related Tweets
Imran, Ali Shariq; Daudpota, Sher Muhammad; Kastrati, Zenun; Batra, Rakhi (Peer reviewed; Journal article, 2020)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 ... -
Detecting suicidality on social media: Machine learning at rescue
Rabani, Syed Tanzeel; Ud Din Khanday, Akib Mohi; Khan, Qamar Rayees; Hajam, Umar Ayoub; Imran, Ali Shariq; Kastrati, Zenun (Journal article; Peer reviewed, 2023)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 ... -
Emotions don't lie: A multimodal approach to Personality Prediction
Taralrud, Hans Petter Fauchald (Master thesis, 2023)Å oppdage de riktige jobbsøkerne som passer med stillingsbeskrivelsen er avgjør-ende for organisasjonene sin suksess og vekst. Siden personligheten til kandidater er en akseptert indikator på jobbprestasjon, jobbtilfredshet ... -
The enlightening role of explainable artificial intelligence in medical & healthcare domains: A systematic literature review
Ali, Subhan; Akhlaq, Filza; Imran, Ali Shariq; Kastrati, Zenun; Daudpota, Sher Muhammad; Moosa, Muhammad (Peer reviewed; Journal article, 2023)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, ... -
Evaluating Polarity Trend Amidst the Coronavirus Crisis in Peoples’ Attitudes toward the Vaccination Drive
Batra, Rakhi; Imran, Ali Shariq; Kastrati, Zenun; Memon, Abdul Ghafoor; Daudpota, Sher Muhammad; Shaikh, Sarang (Peer reviewed; Journal article, 2021)t 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 ... -
The impact of synthetic text generation for sentiment analysis using GAN based models
Imran, Ali Shariq; Yang, Ru; Kastrati, Zenun; Daudpota, Sher Muhammad; Shaikh, Sarang (Peer reviewed; Journal article, 2022)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 Impact of Translating Resource-Rich Datasets to Low-Resource Languages Through Multi-Lingual Text Processing
Memon, Abdul Ghafoor; Imran, Ali Shariq; Daudpota, Sher Muhammad; Kastrati, Zenun; Somro, Abdullah; Batra, Rakhi; Wani, Mudasir Ahmad (Journal article; Peer reviewed, 2021) -
Improving Document Classification Using Ontologies
Kastrati, Zenun (Doctoral theses at NTNU;2018:44, Doctoral thesis, 2018)We are living in the age of internet where massive amount of information is produced from various digital resources on daily basis. The information of these resources is typically stored in unstructured textual format such ... -
Integrating word embeddings and document topics with deep learning in a video classification framework
Kastrati, Zenun; Imran, Ali Shariq; Kurti, Arianit (Journal article; Peer reviewed, 2019)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 ... -
MOOC dropout prediction using machine learning techniques: Review and research challenges
Dalipi, Fisnik; Imran, Ali Shariq; Kastrati, Zenun (Chapter, 2018)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 ... -
Performance analysis of machine learning classifiers on improved concept vector space models
Kastrati, Zenun; Imran, Ali Shariq (Journal article; Peer reviewed, 2019)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 ... -
The Potential of Machine Learning Algorithms for Sentiment Classification of Students’ Feedback on MOOC
Edalati, Maryam; Imran, Ali Shariq; Kastrati, Zenun; Daudpota, Sher Muhammad (Peer reviewed; Journal article, 2021)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 ... -
Predicting Personality in Job Interviews By leveraging Emotion Recognition from Multi-Modal Sentiment Analysis Models
Abdi-Salah, Abdulfatah (Master thesis, 2023)Den økende bruken av digitale intervjuer i ansettelsesprosessen har akselerert forskning på metoder som kan forbedre deres effektivitet. Rekrutterere benytter seg av AI-metoder for å få en dypere forståelse av kandidater ... -
Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study
Kastrati, Zenun; Dalipi, Fisnik; Imran, Ali Shariq; Pireva, Krenare; Wani, Mudasir Ahmad (Peer reviewed; Journal article, 2021)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 ... -
Sentiment Polarity and Emotion Detection from Tweets Using Distant Supervision and Deep Learning Models
Kastrati, Muhamet; Biba, Marenglen; Imran, Ali Shariq; Kastrati, Zenun (Journal article; Peer reviewed, 2022) -
SentiUrdu-1M: A large-scale tweet dataset for Urdu text sentiment analysis using weakly supervised learning
Memon, Abdul Ghafoor; Imran, Ali Shariq; Daudpota, Sher Muhammad; Kastrati, Zenun; Shaikh, Sarang; Batra, Rakhi (Peer reviewed; Journal article, 2023)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 ... -
Soaring Energy Prices: Understanding Public Engagement on Twitter Using Sentiment Analysis and Topic Modeling With Transformers
Kastrati, Zenun; Imran, Ali Shariq; Daudpota, Sher Muhammad; Memjon, Muhammad Atif; Kastrati, Muhamet (Peer reviewed; Journal article, 2023)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 ... -
A Systematic Literature Review on Text Generation Using Deep Neural Network Models
Fatima, Noureen; Imran, Ali Shariq; Kastrati, Zenun; Daudpota, Sher Muhammad; Soomro, Abdullah (Peer reviewed; Journal article, 2022)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 ...