基于海量异构数据索引语义查询的关键模型研究
Research on key model of index semantic query based on massive heterogeneous data

基于非结构化数据海量、异构、多元、内容丰富、不容易描述的特点，从海量异构数据特征模型角度，对非结构化数据的混合查询问题进行分析. 重点论述非结构化数据特征建模的关键技术，可以有效地解决网络大数据背景下的数据检索效率，从整体上提高数据检索的速度和效率.
Based on the characteristics of unstructured data，this paper makes an analysis into its hybrid query problem from the perspective of massive heterogeneous data feature model. It fully illustrates the key technologies of unstructured data feature modeling. This paper helps to improve the speed and efficiency of data retrieval as a whole under the background of big network data