Computational Analysis and Ontology Construction of Legal Texts

Bys: Bin Zhang and Manman Cheng

This research develops a framework for transforming legal texts into knowledge graphs via topic-driven ontology construction, integrating Latent Dirichlet Allocation with OWL/RDF formalization.Methodology: (1) text preprocessing, (2) LDA-based topic discovery, (3) topic-to-ontology translation, (4) instance mapping, (5) relationship establishment, (6) validation. Technical implementation uses OWL/RDF for specification and SPARQL for querying.Applications include intelligent legal question-answering, automated conflict detection, and legislative impact analysis. Integration of topic modeling with ontology engineering reduces annotation costs while maintaining fidelity. Domain-specific models (LEGAL-BERT) enhance performance but require expert validation.This work bridges statistical analysis and formal representation, advancing legal infrastructure from documents to graph-based systems.

• Format: Paperback
• Language: English
• ISBN: 6209851479
• ISBN13: 9786209851476
• Release Date: April 2026
• Publisher: LAP Lambert Academic Publishing
• Length: 412 Pages
• Weight: 1.21 lbs.
• Dimensions: 9.0" x 0.9" x 6.0"