# On Ontology-Based Tourist Knowledge Representation and Recommendation
## 1 Introduction
A number of researchers have examined tourist recommendation systems. For example, [PERSON] and [PERSON] (2015) used experts and the Delphi method to solicit tourist attraction information [19], but this approach required a lot of time and effort. To avoid this disadvantage, the current study primarily uses information technology to analyze OTR in a fast, efficient manner. In addition, [PERSON] and [PERSON] (2013) applied statistical analysis to analyze the information contained in an online platform, Booking.com, in order to recommend hotels [20]. However, the application of statistical analysis to tourist knowledge depends on the data being used, which may not be up-to-date. This study overcomes this problem by applying sentiment analysis to analyzing OTR content, and thus the latest appraisals of tourist attractions can be found. Among the current studies of tourist attraction recommendation systems [19; 20; 21; 22; 23], none has applied OTR and ontology. The value of knowledge-based systems lies in the sharing and managing mechanism. Developing a brand new traveling recommendation mechanism is the primary purpose of the study. Through ontology, OTR was transformed into a traveler knowledge structure. The structure can help us to effectively carry out tourist knowledge management. In addition, the tourist knowledge structure was also used to design a method for recommending tourist attractions. The method put tourist knowledge into effective sharing and use. Ontology has been a well-developed technique. Constructive ontology, deductive ontology, and natural language analysis were applied in the development of the recommendation mechanism. Nonetheless, current tourist attraction recommendation systems on the market have not used constructive ontology, deductive ontology, and natural language analysis. The study utilized well-developed technology to share and manage tourist knowledge, and this is what set this study apart from others. OTR is a kind of tacit knowledge. There are few tourist attraction recommendation systems that adopted tacit knowledge. The reason is that the collection, analysis, management, and application of tacit knowledge is more complicated. Tacit knowledge is adopted in this study. This has shown the value of this study in contributing to the application of tacit knowledge in this field. Therefore, this study developed an ontology-based tourist knowledge representation and recommendation mechanism to carry out appraisal analysis of OTR content. Through the collection of positive appraisals related to tourist attractions, tourist knowledge structures were constructed based on ontology. These tourist knowledge structures were then used to develop a tourist knowledge representation and recommendation mechanism. This study thus has the following aims: (i) designing an OTR and eWOM management framework; (ii) constructing an ontology-based tourist knowledge representation and recommendation procedure; (iii) providing an ontology-based tourist knowledge representation and recommendation method; and (iv) developing an ontology-based tourist knowledge representation and recommendation mechanism. This paper is organized as follows. In Section 2, the differences between OTR and ontology characteristics are analyzed, and the results are then used to develop an ontology-based tourist knowledge representation and recommendation model. In Section 3, the methodology used for designing and developing the ontology-based tourist knowledge representation and recommendation procedure is explained. In Section 4 the model is developed and tested to examine its practicality. Finally, the conclusions of this work are presented in Section 5, along with recommendations for future research.