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
This study's scope includes the development of a Question Answering System for COVID-19 and a review of that system. This is unlike previous work in biomedical QAS, which primarily targets technical users. This work lean…
Effective prioritization of software requirements is essential for reducing project risks, optimizing resource allocation, and ensuring timely delivery. Conventional approaches such as Analytic Hierarchy Process (AHP) an…
The exponential growth of applications in digital and information system domains has made the identification of qualified candidates increasingly complex, resulting in longer and less efficient recruitment processes. Rec…
Cross-lingual sentiment analysis (CLSA) has become increasingly important in natural language processing and machine learning, enabling the understanding of opinions across diverse linguistic communities, particularly in…
Radiology reports encode critical clinical observations from medical imaging in an unstructured textual form that is central to modern clinical diagnosis and decision support. In this context, natural language processing…
Machine-Readable Code (MRC) and Machine-Readable Regulations (MRR) enable the conversion of complex regulations into structured formats such as JSON, XML, and X2RL, allowing machines to parse and interpret regulatory tex…
Sentence embedding is a very important technique in most natural language processing (NLP) tasks, such as answer generation, semantic similarity detection, text classification and information retrieval. This technique ai…
The rapid growth of e-commerce has changed the way people engage with businesses, notably in the food industry. For the Muslim community, guaranteeing Halal conformity in digital transactions is critical. This study prov…
Cyberbullying is one of these challenges that are most found among the younger users of social media which affects the mental health. Artificial Intelligence (AI) is rapidly developing and has enormous potential to mitig…
Text mining methods often rely on a single data source or simple word frequency statistics, making it difficult to capture multi-source text semantic associations and local contextual dependencies, resulting in poor mini…
