基于本体的P2P复杂搜索

传统的DHT-P2P系统有一定的局限性，如基于单特征词搜索，计算机不理解用户搜索请求的含义等。对基于本体的P2P复杂搜索进行了研究。应用向量空间模型理论去描述文档，同时对P2P标识符空间进行分割，使相似文档在邻近的节点范围内聚集，不但解决了多特征词复杂搜索的问题，而且提高了搜索的速度。利用本体知识的帮助去理解用户的搜索请求，合理扩大搜索范围，避免搜索结果出现遗漏。实验结果表明，依据该理论构建的仿真系统实现了复杂搜索，搜索速度较快，提高了查全率，且节点达到了较好的负载平衡。

P2P complex search based on Ontology

The traditional DHT-P2P system has its limitations. It can only perform single keyword search and cannot understand the meanings of users' requests. P2P complex search based on Ontology was studied. Vector Space Model theory was used to describe documents. And the P2P identifier space was divided to gather the similar documents at adjacent nodes. Therefore, the problem of multi-keywords complex search was solved, and in the mean time, the search process was speeded up. With the help of Ontology, the whole system could understand users' requests better and broaden the searching scope reasonably to avoid missing partial result. Simulated system partially implemented by this theory has accomplished complex search, accelerated the search process, and improved the recall. In addition, it has achieved a better load balance of nodes.