The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
Natural language processing (NLP) is the field of computer science focused on enabling computers to understand, interpret, and generate human language. Core tasks include tokenization, part-of-speech tagging, syntactic parsing, named entity recognition, machine translation, text summarization, question answering, and sentiment analysis. Early NLP systems relied on rule-based grammars and statistical language models; current approaches are dominated by transformer-based architectures and large language models pretrained on extensive text corpora and fine-tuned for specific tasks. Active research increasingly targets efficient attention mechanisms, including linear and sparse attention, to reduce the heavy compute and memory costs of standard transformers, alongside work on multilingual and low-resource languages, model bias, and factual reliability in generated text. Applications include chatbots and virtual assistants, automated document analysis, information extraction from unstructured text, and cross-lingual translation systems. As an open-access natural language processing journal (an NLP journal), IJACSA publishes research on language models and applied systems evaluated across multiple languages and domain-specific text corpora.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed October 2026
Agile methodologies are considered revolutionary approaches in the development of systems and software. With the rapid advancement of artificial intelligence, natural language processing, and large language models, there…
Figurative language, especially sarcasm, poses strong challenges for Natural Language Processing (NLP) models because of its implicit, context-sensitive nature. Both traditional and transformer models tend to find it dif…
Sentiment analysis is a fundamental task in natural language processing with wide-ranging applications, from customer feedback monitoring to healthcare and social media analytics. While recent research has mainly emphasi…
Sentiment classification is a core task in natural language processing (NLP), enabling automated interpretation of opinionated text across domains, such as social media, e-commerce, and healthcare. While numerous models…
The existence of voluminous multilingual sources on the web in different fields creates numerous issues, including violations of intellectual property rights. For that, the multilingual plagiarism or cross-language plagi…
In corporate e-training environments, traditional metrics like course completion and quiz scores often fail to reflect actual job performance. Rich insights are embedded in unstructured textual feedback, yet they remain…
An Artificial Intelligence-driven child learning system with a Machine Learning and Natural Language Processing-based approach to dynamically personalize educational experiences for children is proposed in this study. Us…
Cross-site scripting (XSS) attacks remained among the most persistent threats in web-based systems, often bypassing traditional input validation techniques through obfuscated or embedded scripting payloads. Existing dete…
The integration of Big Data and Artificial Intelligence (AI) is fundamentally transforming how labor markets are analyzed, predicted and managed. Despite significant advances in using these technologies for workforce ana…
Large Language Models (LLMs) have demon-strated remarkable capabilities in generating human-like text; however, their effectiveness in abstractive summarization across diverse domains remains underexplored. This study co…
