| Title | On the Network and Topological Analyses of Legal Documents Using Text Mining Approach |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Somsakul, Supawit, Prom-on, Santitham |
| Conference Name | 2020 1st International Conference on Big Data Analytics and Practices (IBDAP) |
| Keywords | Big Data, composability, Computational modeling, Document Mining, graph analysis, Graph Clustering, Human Behavior, human factors, Law, Metrics, network science, pubcrawl, Scalability, text analysis, text analytics, text mining |
| Abstract | This paper presents a computational study of Thai legal documents using text mining and network analytic approach. Thai legal systems rely much on the existing judicial rulings. Thus, legal documents contain complex relationships and require careful examination. The objective of this study is to use text mining to model relationships between these legal documents and draw useful insights. A structure of document relationship was found as a result of the study in forms of a network that is related to the meaningful relations of legal documents. This can potentially be developed further into a document retrieval system based on how documents are related in the network. |
| DOI | 10.1109/IBDAP50342.2020.9245615 |
| Citation Key | somsakul_network_2020 |
On the Network and Topological Analyses of Legal Documents Using Text Mining Approach