The Development of an Ontology for Information Retrieval about Ethnic Groups in Chiang Mai Province

This study aims to develop the semantic ontology of information knowledge about ethnic groups by analyzing information from the collection of documentary sources from libraries, research, and the museum for learning about people on the highlands located in Chiang Mai Province. The study is based on the classification theory of ethnic groups in Chiang Mai Province with the intention of establishing the relationship between knowledge structure regarding ethnic groups. The study procedures consist of three stages: 1)Establishing ontology requirements from online data to analyze the data of the keyword from the research database of Chiang Mai University Library's Online Information Resource Database (OPAC) and Ratchamangkhalaphisek National Library, Chiang Mai to group the words by studying information resources in Thai language, such as books, textbooks, research papers, theses, research articles, academic articles, and reference books related to ethnic groups. Stage 2) Designing classes, defining main classes, subclasses, hierarchies, and properties in order to establish the relationship of data in each class using the Protégé program. Stage 3) Ontology evaluation, which is divided into two parts: an expert's evaluation of the suitability of the ontology structure using the Inter-Class Relational Accuracy Assessment Scale and an examination of ethnic grouping data. The findings reveal that specifying, definition, scope, and objectives of development are appropriate (average score = 0.97) in three areas: grouping and ordering of classes within the ontology (score value = 0.98), defining affinity names and class properties (score value = 0.96), and suitable overall ontology content (score value = 0.97).

@article{Julrode2022,
  title     = {The Development of an Ontology for Information Retrieval about Ethnic Groups in Chiang Mai Province},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {10},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Phichete Julrode and Thepchai Supnithi},
  doi       = {10.14569/IJACSA.2022.0131082},
  url       = {https://doi.org/10.14569/IJACSA.2022.0131082}
}