Towards Improving the Knowledge Representation and Searching of Manchu Costume Culture: An Ontology-based Method with APP Implementation

Abstract

Costume culture traditionally spread through words of mouth or paper, which is not able to support systematic and extendible knowledge representation, as well as semantic searching. Hence, in order to improve the knowledge representation and searching of Manchu costume culture, an ontology-based method with semantic searching is proposed in this paper. Firstly, Manchu costume was classified and indexed according to professional view of ethnic study based on surveys and literatures. Secondly, the ontological knowledge base of Manchu costume was constructed using Protégé and OWL software tool. Thirdly, the search algorithm and engine of Manchu costume was designed. Then implemented by JAVA language, integrated with Jena inference engine as well to improve the matching performance. Finally, an APP of Manchu costume was developed with HTML5 language on APICloud ECS to validate the proposed method. The contribution of this paper is threefold: a) constructing a knowledge base of Manchu costume based on ontology technique, which is extendible and generalizable to other national costume; b) proposing the semantic searching engine based on rule-based reasoning using SPARQL query language; c) implementing an APP for validating the proposed method for improving the knowledge representation and semantic searching of costume culture.