煤矿本体的语义相似性研究

为了在信息检索中，从语义层面全面理解用户查询意图，提高信息的查全率和查准率，提出了基于本体的语义相似性和相关性计算方法。该算法充分考虑了本体模型结构的特点和本体间语义距离、本体密集度等因素对语义相似性的影响，提高了信息检索性能。以煤炭矿井工程的知识体系为例，建立了本体库模型，并设计了本体库的树状内存数据结构。通过实验仿真计算验证了本体相似性算法的有效性。

Research on the Semantic Similarity of Coalmine Ontology

In order to comprehensively understand the user's query intention and improve the precision rate and recall rate in the information retrieval, we proposed an ontology-based semantic similarity algorithm and an ontology-based semantic relevance algorithm. In the algorithms, we fully considered the characteristics of the ontology model and the effect of semantic distance and ontology density on the semantic similarity. Based on the knowledge system of the coalmine project, we established an ontology library model, and designed a tree structure to store ontology library in the memory. By simulation, we verified the ontology similarity algorithm is effective.