Creative Travel Idea Generation Based on Semantic Web and Lateral Thinking

As society is developing and people's living standards are increasing, tourism becomes one of the popular choices to relax. Meanwhile, the general travel information from traditional travel related websites are hard to satisfy the customers' requirements. The main challenge for traditional websites is how to provide creative ideas to customers. In order to solve this problem, this paper presents algorithms to achieve customers' target. This project can be divided into three parts. The first part is to enrich and to analyse the input keywords by semantic web. The second part is to general raw ideas and relevant ideas by an inference engine and lateral thinking. The final part is to generate creative ideas by creative techniques.