Natural Language Processing Framework

Natural Language Processing (NLP) frameworks aim to build computational systems that understand and process human language, enabling diverse applications. Current research emphasizes developing robust and explainable models, often leveraging transformer architectures like BERT, for tasks ranging from sentiment analysis and bias detection to personalized recommendations and medical diagnosis using text data. These frameworks are proving valuable across various fields, improving information retrieval, enhancing user experiences, and facilitating more nuanced analyses of complex textual data in areas like healthcare, journalism, and social sciences.