Legal-Onto Model for Efficient Land Law Updates in Vietnam

In the rapidly evolving economic and social landscape of Vietnam, land remains a pivotal resource, crucial for economic growth and social stability. The recent enactment of the Land Law 2024, which supersedes the 2013 legislation, necessitates continuous updates for land users, investors, and regulatory authorities to ensure compliance and optimize land utilization. Traditional legal information retrieval systems are constrained by keyword-based searches and pre-set responses, which are inadequate for addressing specific user queries or rapidly integrating new legislative updates. This paper presents an advanced technological solution employing the Legal-Onto model to represent and update legal knowledge. The Legal-Onto model, inspired by relational ontology and keyphrase graphs, captures the semantic content of legal documents. By employing natural language processing techniques, the system automatically compares old and new legal texts, identifying differences at the article, point, and clause levels. This enables efficient updates and provides a valuable tool for legal professionals. It demonstrates the potential of artificial intelligence in legal contexts, offering a more effective and accessible approach to legal information.