提出了一种对语义网上的本体进行检索和排序的新方法ARRO(an Approach for Retrieval and Ranking for the On-tology),其核心思想是通过对本体进行解析产生逻辑三元组.再在三元组的基础上进行逻辑推理,形成概念的逻辑视图,然后通过排序公式对相关本体进行检索和排序.这种通过逻辑视图和三元组对本体进行检索和排序的方法可以有效的进行逻辑推理,并提高检索效率,从而解决在传统的基于关键字的信息检索中只能从句法上对关键字进行分析,无法将推理和检索相互结合,互相促进的问题.本文对ARRO进行了测试,结果验证了其实用性和有效性.
In order to solve the problem of information retrieval on the semantic web, a new semantic information retrieval （SIR） model for searching ontologies on the semantic web is proposed. First, SIR transformed domain ontologies into global ontologies. Then semantic index terms were extracted from these global ontologies. Based on semantic index terms, logical inferences can be performed and the logical views of the concept can be obtained. These logical views represent the expanded meaning of the concept. Using logical views, SIR can perform the information retrieval and inferences based on the semantic relationships in the documents, not only on the syntactic analysis of the documents. SIR can significantly enhance the recall and precision of the information retrieval by the semantic inference. Finally, the practicability of the SIR model is analyzed.
