Reasoning Service For Rule-based Tourism Ontology

With the explosion of Internet travel resources and the increasing demands of tourists on the travel information, the current keyword-based string-matching skill and content-classified directory search cannot fully meet the needs of users, since the machine could not properly understand the semantics of the information, and the feedback returned by machine is not so accurate so that the tourists is difficult to find the related resources that they need. Internet Travel Information is presented in the form of natural language to humans with intelligence to understand them, but the information lacks of a unified semantics standard to describe it, so it is necessary to develop a machine system that could automatically process the internet travel information to satisfy the tourists. Therefore, how to use the machine automatically organize and manage large amounts of information that facilitated the visitors to grasp the information and provide effective services to tourists as an important and research content.To achieve this function of automatic machine processing, the Semantic Web as an extension of the current World Wide Web provides a good basis for such a platform. The information in Semantic Web has been given a clear semantics that machine knows, the machine can handle this information with the semantics and make the interaction and cooperation between machines and humans possible. In recent years, Semantic Web research focuses on ontology, ontology as a semantic knowledge level in the conceptual model described in the information modeling tool, has become one of the core of the Semantic Web. Ontology research in recent years has made great progress, and ontology is more and more widely applied. As a new management structure of knowledge, people can gain knowledge from the ontology, and in the ontology, a number of important knowledge is often hidden to be given, so the key to implement the Semantic Web is to develop a ontology reasoned to derive the hidden knowledge. Based on this, the paper design and implement reason system based on the tourism ontology.This paper is mainly about how to use the ontology describe language to construct ontology and ontology-based reasoning in the tourism domain ontology system, for this realization the paper launches a more intensive systematic work, the paper mainly divided into the following parts: First of all, for the characteristics of China's tourism industry, tourism and related industries expertise, norms and standards of provision in the state, through background skill of creating a ontology, this paper determines the background and the resources selection of the tourism ontology, and analyzes the structural hierarchy and property relationships exist among tourism knowledge, also gives the definition of the common terms and concepts in tourism areas to make construction of tourism ontology more explicit and clear; by referring to other areas of ontology construction, this paper sums up the tourism development process and proposes an approach of tourism domain ontology construction; in the end, a tourism ontology is created by that method and ontology describe language.Then, in order to ensure the knowledge consistency of the established tourism ontology, after a detailed comparison of four popular inference engine and the tableau reason algorithm to analyze principle and advantages of the Pellet inference engine, this paper finalizes Pellet inference engine to check the knowledge consistency of tourism ontology from the aspects of TBOX and ABOX, respectively. Through this step, the paper gets a consistent tourism ontology without knowledge conflict.Furthermore, on the basis of the consistent tourist ontology which was set up previously, it introduces the ontology rules language SWRL and its decidable sub-language DL-safe in the semantic web. After surveying and analyzing the tourist information the tourists care about and the actual tourist demands of the tourists, it formulate a set of SWRL rules of tourist ontology through the SWRL language, which includes the issue of different groups of people to buy half-price tickets, the recommendation of the best traveling routes, the weather guides during the traveling.Finally, combining the consistent tourist ontology and the SWRL rules extended from the basis of the tourist ontology, through the analysis of the ontology rules reasoning engine Jess, especially the Rete algorithm achieved internally, it converts the tourist ontology and SWRL rules into the internal format which the reasoning engine can identify as well as the reasoning process of the pattern matching algorithm from the prioritizing of the rules and then returns the results, which includes the knowledge already existing in the ontology and the tacit knowledge from the reasoning of the ontology. This article ultimately designed and realized the reasoning system based on tourism.The meaning of the paper is to establish a tourism ontology through the analysis of the knowledge in the field of tourism, to set up a series of extending rules on the basis of the ontology according to the information of the users with combination of SWRL semantic rules as well as to further analyze the knowledge and rules of the ontology through the reasoning engine which reflects the automatic reasoning intelligence of this system and saves the memory space effectively and improves the efficiency of the searching. The more important is that the article tries to combine the knowledge in reality with the semantic web of the ontology and set up rules according to the demands of the users on the basis of it, do the reasoning query and return the information to the users. It, to some extent, enlarges the previous function that doing the query largely depends on the key words, and can supply the users of the information they want quickly and correctly. With the development and popularity of the semantic web, the prospect to combine it with reality is brighter. The integrality of the rules and the efficiency and effectiveness of the reasoning still need supplement and improvement as the extension of this paper.