Extraction of Importance activities from Supreme Court judgments to generate police daily reports

Main Article Content

Sukree Sinthupinyo
Napat Ngamsodsai

Abstract

This research aims to solve the problem of the police daily record and help inquiry officers record the report conveniently. We extracted significant keywords, from Supreme Court’s judgments and related cases, to find the relationship between individual words. Moreover, to identify those keywords, we apply social network graph techniques; Betweenness Centrality, PageRank, Degree Centrality, Closeness Centrality, and Eigenvector Centrality. To create the daily report, we designed a procedure for traversing a summarized graph. As a result, we got a gist which can be taken as detail or circumstance to show in the daily report.

Article Details

Section
บทความวิจัย

References

National Statistical Office, Ministry of Digital Economy and Society, Number of Population from Registration by Age Group, Region and Province: 2012 – 2021. Available Online at http://statbbi.nso. go.th/staticreport/page/sector/th/01.aspx, accessed on 14 November 2022.

W. Aroonmanakun, and T. Champaiboon. Thai Dependency Tree Bank data supervision manual according to Universal Dependencies v.2, Centre for Research in Speech and Language Processing (CRSLP), 2020.

N. Makaje, and A. Intarasit. "Basic Graph Theory and Its Applications," The Journal of KMUTNB, Vol. 25, No. 3, September-December, 2015.

M. Patchimnan. "Social Network Analysis and Organizational Communication Research," King Prajadhipok's Institute Journal, Vol. 15, No. 3, pp. 5-18, 2017.

S. B. Lawrence Page, The PageRank Citation Ranking: Bringing Order to the Web, 1999.

M. Franceschet, "Network Science," Department of Mathematics and Computer Science University of Udine, Udine, 2014.

S. Praking, S. Phimcharee, P. Thodthong, P. Kotsuwan, and P. Utaranakorn , "The centrality of social networks for exchanging information of group members: A case study of growing safe vegetable group at Ban Mo, Sam Sung district, Khon Kaen province," Khon Kaen Agriculture Journal, Vol. 47, pp. 1065-1070, 2019.

J. Leskovec, M.F. Natasa, and G. Marko. "Extracting Summary Sentences Based on the Document," 2005.

K. Kastriot, and O. Milenko. Extractive approach for text summarization using graphs, Ljubljana, Slovenia: University of Ljubljana, Faculty of Computer and Information Science, 2021.

M. P. J. P. R. H. Andry Alamsyah, "Network Text Analysis to Summarize Online Conversations for Marketing Intelligence Efforts in Telecommunication Industry," In 2016 4th International Conference on Information and Communication Technology (ICoICT), Bandung, Indonesia, 2016.

H. Christian, M.P. Agus, and D. Suhartono. Single Document Automatic Text Summarization using Term Frequency-Inverse Document Frequency (TF-IDF)." ComTech Computer Mathematics and Engineering Applications, Vol. 17, No. 4, pp. 285-294, December, 2016.