Research ArticleOpen accessIn the keywordsCustomized Named Entity Recognition Using Bert for the Social Learning Management System Platform CourseNetworkingKayal Padmanandam, KVN Sunitha, Behafarid Mohammad Jafari et al.Named Entity Recognition (NER) is an information extraction task and one of the most researched applications to extract knowledge from massive data. Conventional NER systems identify predefined entities like name, person, location, organization, time, etc. However, there is a limitation to identifying user-defined entities that are specific to an application. This challenge introduces the concept of customized NER. For instance, … …Journal of Computer Science, Vol. 20, Issue 1 · 15 Dec 2023 · 6,985 accessesView PDFCite
Research ArticleOpen accessIn the abstractUzNER: A Human-Reviewed Benchmark for Uzbek Named Entity Recognition With Gazetteer-Augmented Transformer ModelsBobur Saidov, Vladimir Barakhnin et al.UzNER-100K is a large-scale human-reviewed benchmark for Uzbek named entity recognition with 100,000 training sentences, 18 fine-grained entity types and 200,083 entity mentions across 114,269 sentences in total. The corpus was constructed through an LLM-assisted, expert-reviewed annotation pipeline that achieved strong reliability on the main audit subset while substantially reducing corpus-construction effort. The benchmark includes a standard test split, a … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,308 accessesView PDFCite
Research ArticleOpen accessIn the abstractArabic Fake News Detection Across Generational Text Representations: From Traditional Models to Transformer-Based MethodologiesNoor M. AlkudahThe rapid proliferation of fake news on Arabic social media has amplified societal and political risks, yet research on automatic detection in Arabic remains limited due to scarce datasets, morphological complexity, and underexplored preprocessing strategies. This study presents a comprehensive benchmark for Arabic fake news detection, unifying seven Machine Learning (ML) algorithms, three Deep Learning (DL) models, and a transformer-based … …Journal of Computer Science, Vol. 22, Issue 4 · 17 Apr 2026 · 1,873 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving Arabic Named Entity Recognition with a Modified Transformer EncoderHamid Sadeq Mahdi Alsultani, Ahmed H. AliwyThis article investigates the use of a transformer encoder for Arabic Named Entity Recognition (NER). The classic transformer that was originally proposed for machine translation adopts the absolute sinusoidal position embedding which is aware of distance but unfortunately is not aware of the directionality. However, in the NER task, both distance and orientation are crucial. Therefore, in this study, instead … …Journal of Computer Science, Vol. 19, Issue 5 · 10 Apr 2023 · 5,330 accessesView PDFCite
Research ArticleOpen accessIn the abstractBoosting Arabic Named Entity Recognition with K-Fold Cross Validation on LSTM and Bi-LSTM ModelsHamid Sadeq Mahdi Alsultani, Ahmed H. AliwyNamed-Entity-Recognition(NER) is one of the most important Information-Extraction (IE) use cases, whichis used to improve the performance of Natural Languages Processing (NLP) tasks,such as Relation-Extraction (RE), Question-Answering (QA). Recently, Arabic NER is tackled in differentways by researchers. In this study, we assess the performance of two widelyused models, namely, LSTM and Bi-LSTM on the NER task in the Arabic languageand … …Journal of Computer Science, Vol. 18, Issue 9 · 6 Sep 2022 · 6,317 accessesView PDFCite
Research ArticleOpen accessIn the abstractNamed Entity Recognition for Kannada using Gazetteers list with Conditional Random FieldsK. P. Pallavi, L. Sobha, M. M. RamyaNamed Entities (NEs) that exist in the sentences are essential to build Natural Language Processing (NLP) applications for Information Extraction (IE) from large corpora. However, generating a large corpus is challenging for resource poor languages, such as Kannada. Further, there is no annotated corpus available online. The challenges faced in annotating NEs with pre-defined classes are: It is morphologically joined … …Journal of Computer Science, Vol. 14, Issue 5 · 24 Feb 2018 · 8,275 accessesView PDFCite
Research ArticleOpen accessIn the abstractArabic Named Entity Recognition Using Artificial Neural NetworkNaji F. Mohammed, Nazlia OmarProblem statement: Named Entity Recognition (NER) is a task to identify proper names as well as temporal and numeric expressions, in an open-domain text. The NER task can help to improve the performance of various Natural Language Processing (NLP) applications such as Information Extraction (IE), Information Retrieval (IR) and Question Answering (QA) tasks. This study discusses on the Named Entity … …Journal of Computer Science, Vol. 8, Issue 8 · 16 Jul 2012 · 8,676 accessesView PDFCite