Research And Implementation On Tourist Attraction Recommendation System Based On Rule-Based Reasoning

Expert systems based on rule-based reasoning is one of the main branches in the field of artificial intelligence.Its working principle is to obtain rules conclusions by continuously using the rules in the knowledge base to match the facts.In the field of tourism,the process of making travel decisions is also a process in which tourists make inferences about their own needs.Introducing rule reasoning into the tourism field,mining out the rules in the travel decision-making process and using it,automatically processing information and recommending it to users,has a certain application value and meets the development needs of the current tourism industry.The ontology theory is introduced into the tourist attraction recommendation system to represent the information of the tourism resources.Implement more intelligent query services combined with the corresponding expansion rules which can provide the tourists with more comprehensive information and facilitate their planning.At the same time,in order to facilitate tourists to obtain more targeted tourism information from a large number of tourism resources,it is faster and more convenient to formulate outbound travel plans.This paper uses rough set technology to discover potential tourism rules from massive tourism-related information.To build an expert system for tourism areas and provide personalized attractions recommendation programs through tourist demand information.In-depth study of related theories of Rete algorithm,combined with knowledge representation of production rules adopted by the system,construction of the rules inference engine of tourism attraction recommendation system based on Rete algorithm,and propose an effective improvement method to optimize the problem based on the efficiency of the algorithm.The implementation efficiency of the algorithm is improved,thereby effectively improving the work efficiency of the tourist attraction recommendation system.Finally,relying on the structural characteristics of the expert system.Implement tourist attraction recommendation system.Finally,verify the recommendation function with specific examples.