Text clustering applied to data augmentation in legal contexts

arXiv:2404.08683v1 Announce Type: cross
Abstract: Data analysis and machine learning are of preeminent importance in the legal domain, especially in tasks like clustering and text classification. In this study, we harnessed the power of natural language processing tools to enhance datasets meticulously curated by experts. This process significantly improved the classification workflow for legal texts using machine learning techniques. We considered the Sustainable Development Goals (SDGs) data from the United Nations 2030 Agenda as a practical case study. Data augmentation …

abstract analysis arxiv augmentation classification clustering cs.cl cs.lg data data analysis datasets domain experts importance language language processing legal machine machine learning natural natural language natural language processing natural language processing tools power process processing study tasks text text classification tools type