Ontology Reasoning Mechanism And Application In Intelligent Query

In the knowledge-based economy era, people are eager to acquire information efficiently and quickly. The keyword-based conventional query only can give information which is literally matching the condition of users’ queries, but can not find to demand the related domain knowledge. It is difficult to realize the semantic resources sharing.With the development and application of ontology, the ontology query can get other information which is matching the condition in the semantic layer. Because of the data-driven ontology query, there is no implicit knowledge from explicit definitions and declarations. In order to maximize the greatest extent possible to obtain useful information, the ontology reasoning is quite necessary. The compatibility and consistency of ontology library can be determined while implicit knowledge can be explored by ontology reasoning. According to the deficiencies of current technologies, this paper proposes an ontology reasoning mechanism for the users to get more valuable information.Firstly, it can be found that not only the ontology query but also the traditional retrieval has lots of defects and shortcomings, so ontology reasoning has a deep impact on solving query issue. Secondly, a case of urban traffic problems in Xi’an has been used to illustrate how to use query expansion and rule-based reasoning to ameliorate information query and retrieve. Thirdly, a prototypical ontology reasoner system has been designed. The prototypical system mainly includes the data, the semantic query and reasoning engine and so on, it combines query expansion and rules reasoning to assist the ontology reasoner system to achieve intelligent query.In the end, this thesis proposes a new mechanism for case-based ontology reasoning and explains the improvement compared with the conventional one. By using Wiki to improve the users’ experience, it makes the system more interactive and provides a new way for the study of CBR.