Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

95 results for “Language Models”

Set a search alert
Review ArticleOpen accessIn the abstractA Systematic Literature Review on English and Bangla Topic ModelingMd. Basim Uddin Ahmed, Ananta Akash Podder, Mahruba Sharmin Chowdhury, Mohammad Abdullah Al MuminDue to the enormous growth of information and technology, the digitized texts and data are being immensely generated. Therefore, identifying the main topics in a vast collection of documents by humans is merely impossible. Topic modeling is such a statistical framework that infers the latent and underlying topics from text documents, corpus, or electronic archives through a probabilistic approach. It … …Journal of Computer Science, Vol. 17, Issue 1 · 8 Jan 2021 · 8,549 accessesView PDFCite
Research ArticleOpen accessIn the abstractSuVashantor: English to Bangla Machine Translation SystemsMahjabeen Akter, M. Shahidur Rahman, Muhammed Zafar Iqbal, Mohammad Reza SelimThis paper presents the system description of Machine Translation (MT) systems for English-Bangla language pair. Our goal was to create two benchmark MT systems that produce a better quality translation and comparatively higher evaluation score than existing MT systems for English to Bangla. In our experiments, we implemented two baseline MT systems using both statistical and neural methods for the … …Journal of Computer Science, Vol. 16, Issue 8 · 16 Aug 2020 · 7,451 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Review of Adversarial Attacks: ML Techniques, Classification and CountermeasuresBhavesh Kumar Sharma, Sanatan Ratna, Rajiv KumarMachine Learning (ML) and Deep Learning (DL)-based technologies have made significant strides in areas such as computer vision, natural language processing, and autonomous systems. Yet they have been applied in high-stake applications, and have been found to be fragile through adversarial attacks-, maliciously crafted small distortions that fool models into making mistakes. From the pioneering work by Szegedy et al. … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,511 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Context Aware Deep Learning Framework for Multi-Level Arabic Fake News Detection Using Hybrid Linguistic RepresentationsNoor Mahmoud Alkudah, Somia Abufakher, Raja Masadeh et al.The rapid spread of false information on social media has made it even more important to be able to spot false news, especially in Arabic-speaking areas where language is more complicated and news is organized in a hierarchy. Recent research show that deep learning and transformer-based models work well, but most of them only look at performance metrics and don't … …Journal of Computer Science, Vol. 22, Issue 3 · 27 Mar 2026 · 1,577 accessesView PDFCite
Research ArticleOpen accessIn the abstractAraSenti-MARBERT-DynGCN: An Advanced Framework for Sarcasm Detection in Arabic TextBassma M Mousa, Mohammed H. Haggag, Mervat GheithSarcasm detection in Arabic texts is challenging because of the complexity in Arabic morphology, the multitudes of dialects used by native speakers, and its strong reliance on context. The lack of standardized orthography in most written forms of Arabic, combined with the frequent use of colloquialisms and metaphorical expressions, makes the task all the more difficult when trying to detect … …Journal of Computer Science, Vol. 21, Issue 11 · 12 Feb 2026 · 1,575 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Hybrid Machine and Deep Learning Model for Detecting Arabic Phishing EmailsFahad GhabbanPhishing emails are becoming an increasingly popular type of cybercrime on the internet, affecting both businesses and individuals. The attackers generally use various methods to trick victims and extract personal information from them, such as bank details, home addresses, and account information. Many attempts have been proposed to tackle this issue by using filtering mechanisms or automated classification methods which … …Journal of Computer Science, Vol. 22, Issue 1 · 9 Feb 2026 · 1,907 accessesView PDFCite
Research ArticleOpen accessIn the abstractPlant Computational Modelling of Green Amaranth Plant for Investment Analyst using FSPM-GroIMP and Fuzzy LogicBakti Amirul Jabar, Ditdit Nugeraha UtamaFunctional-Structural Plant Modelling (FSPM) isplant modeling that considers morphology, physiology, and statistical data. Oneof the software for FSPM is the Growth-Grammar Interactive Modelling Platform (GroIMP).GroIMP is a Java-based platform using the XL language, which is a languagedeveloped from System-L. This study aims to build a virtual plant model ofgreen amaranth (Amaranthus Sp.) in a hydroponic planting systemfor strategic decision-making. In … …Journal of Computer Science, Vol. 18, Issue 8 · 4 Aug 2022 · 5,996 accessesView PDFCite
Research ArticleOpen accessIn the abstractDistributional Models with Syntactic Contexts for the Measurement of Word Similarity in Brazilian PortugueseEduardo E. Berlitz, Denis A. Araujo, Allan B. Silva et al.The similarity between words constitutes significant support to tasks in natural language processing. Several works use Lexical resources such as WordNet for semantic similarity and synonym identification. Nevertheless, words out-of-vocabulary or missing links between senses are perceived problems of this approach. Distributional-based proposals like word embeddings have successfully been used to meet such problems, but the lack of contextual information … …Journal of Computer Science, Vol. 15, Issue 10 · 31 May 2019 · 6,824 accessesView PDFCite
Research ArticleOpen accessIn the abstractMitigating the Evidence-Related Factors in Automated Fact-CheckingAruna Shankar, Narayanan Kulathuramaiyer, Johari Bin Abdullah, Muthukumaran PakkirisamyThe rapid proliferation of digital misinformation highlights the urgent need for robust automated fact-checking systems that can accurately distinguish truth from falsehood. A persistent challenge for these systems is the occurrence of false positives, where truthful information is incorrectly flagged as misleading due to limitations in evidence assessment, including insufficient evidence, logical inconsistencies, and conflicting information. This research introduces a … …Journal of Computer Science, Vol. 21, Issue 3 · 13 Feb 2025 · 6,000 accessesView PDFCite