结合本体子图的RDF数据关键词分布式搜索
College of Mathematics and Computer Science，Fuzhou University，Fuzhou，Fujian 350116，China

针对现存资源描述框架（RDF）查询方案不能满足日益剧增的海量RDF数据的关键词搜索要求，提出一种面向大规模RDF数据的分布式搜索算法（KDSOS）. 该算法首先结合RDF本体构建查询关键词对应的本体子图集并利用评分函数评分；其次在大规模的RDF数据图上优先搜索评分高的本体子图对应的结果子图，直到找到Top-k结果. 实验结果表明，KDSOS算法在搜索效率和准确率上都具有明显的优势.
Existing RDF query method can not meet the keyword search requirement over increasing massive RDF data，thus this paper proposes keyword distributed search with ontology subgraph(KDSOS) algorithm which supports keyword search over large-scale RDF in a distributed platform. The algorithm first builds ontology sub-graph set for query keywords using RDF ontology and sorts by score function，and then preferentially searches result sub-graph of higher score ontology sub-graph on RDF data graph until find Top-k results. The result of experiment shows that KDSOS algorithm has obvious advantages both on query performance and accuracy