Dwipa ontology II: A semi-automatic ontology population process for Bali Tourism based on the ontology population methodology

In this present study, we have found that the terms of linguistic methods (POS) gives higher relevance than the statistical method (TF-IDF). The relevance value is determined by the value of recall. The highest recall is 87.89. Factors affecting the value is the definition of ‘term’ used as reference in this study that focused on the ‘term’ related to classes and attributes that exist in the initial ontology DWIPA version 1, which is limited to: Attraction, Events, Accommodation and Regency. This limitation has led to the narrow scope of the terms sought from the corpus. This research also managed to populate the DWIPA I semi-automatically based on ontology population methodology. The populated ontology named DWIPA II. This ontology consists of 41 new instances added to the following class/ subclasses: Accommodation, Attraction, Event and Regency. Thus, the total instance of DWIPA II is 193 instances. As a part of ontology population, DWIPA II also evaluated by using description logic (DL) query. The result shown that the DWIPA II is consistent, as the number of DL query is the same as the number of instances in the ontology.