基于查询计算的时态RDF关键词查询

Keyword Query of Temporal RDF Data Based on Query Calculation

随着时态数据的大量增加,如何查询和管理时态数据成为了当前的研究热点.资源描述框架(RDF)作为语义网标准的数据和知识表示语言已经广泛用来表示各种领域的数据,如何表示和查询时态RDF就成为了新的研究焦点.目前的大多数研究都是致力于如何表示时态RDF以及如何能够利用标准的SPARQL引擎查询时态RDF,但是普通用户掌握不了时态RDF数据的查询语言及模式.文章提出了新的关键词查询算法:首先根据时态RDF的特点对时态RDF进行压缩形成摘要图;然后建立两个索引,一个是借助关键词与所在时态实体的索引,本索引首次将关键字中的时间与时态实体进行对应,另一个是应用向前路径搜索优先级索引更快找到top-K子图,将待查询的关键词构建成时态SPARQL查询;最后将时态SPARQL查询转换成标准SPARQL查询,并使用SPARQL搜索引擎执行查询.实验结果表明,本方法查准率优于300METIS、300BFS、1000METI、1000BFS的图查询方法.

With the increase of temporal data,how to query and manage temporal data has become a hot research topic.RDF(resource description framework)has been widely used as a semantic web standard data and knowledge representation language to represent data in various fields.Therefore,how to express and query temporal RDF has become a new research focus.At present most of the research is devoted to how to represent temporal RDF and how to be able to use RDF standard SPARQL query engine tense,but the average user to master the tense RDF data query language and mode.In this paper,a new keyword query algorithm is proposed.First,the temporal RDF is compressed to form summary graph according to the characteristics of temporal RDF.Then,two indexes are built.One is to use the index of keywords and temporal entities,which for the first time corresponds the time and temporal entities in keywords.The other is to use the forward path search priority index to find the top-K subgraph faster,and build the keywords to be queried into temporal SPARQL query.Finally,temporal SPARQL queries are converted into standard SPARQL queries and executed using SPARQL search engine.Experimental results show that the accuracy of this method is better than that of 300 METIS,300 BFS,1000 METI and 1000 BFS.