Ontological recommendation multi-agent for Tainan City travel

Due to the gradual increase in travel, the travel agent plays an important role in both planning and recommending a personalized travel route. Tainan City, located in the southern Taiwan, is famous for its abundant historic sites and delicious snack food, and it has been one of the top tourist attractions in Taiwan for years. In this paper, we propose an ontological recommendation multi-agent for Tainan City travel. The core technologies of the agent contain the ontology model, fuzzy inference mechanism, and ant colony optimization. The proposed agent can recommend the tourist a personalized travel route to enjoy Tainan City according to the tourist's requirements. It includes a context decision agent and a travel route recommendation agent. First, the context decision agent finds a suitable location distance, counts the context relation, and infers the context information based on the tourist's requirements and Tainan City travel ontology. Next, the travel route recommendation agent is responsible for finding a personal-ized tour and plotting this travel route on the Google Map. Finally, the tourist can follow the personalized travel route to enjoy the cultural heritage and the local gourmet food during his stay at Tainan City. The experimental results show that the proposed approach can effectively recommend a travel route matched with the tourist's requirements. In recent years, due to the growing number of travelers, a wide range of information such as the tourist attractions and local gour-met food are posted on the Internet to appeal to the tourists. However , it is not easy for a tourist to search the information what exactly he really wants from a large amount of information available on the Internet. Because of this, if there is an agent to help with this heavy work, then it is sure both to reduce travel agency's workload and to accelerate the speed of tourist's getting the travel information. What the tourist or the travel agency only does is just to list his travel requirements. Later, the agent would recommend a route of travel to make the tourist enjoy his trip. Also, Tainan City is a city which features its abundant historic sites, cultures, delicious snack food, ecological environment, and heritage. Therefore, we combine Tainan City tourism with some core techniques like the ontology, fuzzy inference, and ant colony optimization to propose an ontological recommendation multi-agent for Tainan City travel. Ontology is a conceptualization of a domain into a human …