The development of ontology is one important research area in the digital humanities. This study aims at creating a semantic search system for traditions common culture in the Greater Mekong Subregion (GMS) to solve problems in semantic gaps. This paper presents the second phase of the main research. It will present how to develop ontologies for the traditions and common culture in the GMS to gain a perspicuous understanding of the traditions and common culture of those countries in the region. A theoretical concept of seven steps for ontology development was applied by using an ontology editor called Hozo Ontology Editor. The main ontology found in this study included 15 main classes: common culture, history, belief, purpose, location, ritual, activity, literature, values, place, time, principle, person, equipment, and ethnic group. Traditions common culture is a subclass of common culture classes that were found to be related to all classes in ontology. This ontology will be useful for developing a semantic search system of the traditions common culture of the GMS in the next steps of the main study.

This article presents the development of a semantic search system for the common cultural traditions of the Greater Mekong Subregion, which has been studied using common cultural tradition data from Thailand, Laos, and Cambodia. Our system presents the implementation of semantic search to solve the problem of semantic gaps in common cultural characteristic concepts for information access and retrieval. The field of cultural heritage management represents a growing area of research that contains valuable information for users, researchers, and domain experts. Finding information on traditions or cultures of interest among unstructured materials requires a laborious search process. In this paper, we demonstrate how to extract semantic entities and relationships represented in the information using the theory of information science, specifically the Knowledge Organization (KO) approach, which involves determining the concepts and semantic relations of a particular issue and establishing their relations with relevant concepts. It serves as a foundation for knowledge structure development and ontology development, which contribute to effective information searching and knowledge access. The system was developed based on systematic ontology using the Hozo Ontology Editor and Database and ontology mapping using the Ontology Application Management (OAM) framework, which helps distinguish between relevant and irrelevant data, thereby leading to search effectiveness. To cut down on the time wasted in browsing and searching, reduce associated user frustration, and support the research of domain experts, more selective user access is needed.