中文摘要：

针对大量水利元数据共享需要构建搜索引擎的问题，普通用户对水利元数据领域知识的认知存在缺陷，需要引入一种探索式的访问技术准确地表达出检索请求，以实现元数据检索功能。分面搜索是一种探索式的检索方式，根据物体的多维属性，对搜索结果进行聚类，所以用户可以选择分面值对搜索结果筛选过滤。随着水利元数据的增加及水利元数据异构化程度的提高，分面的数量也不断增加。如果把所有的分面都显示给用户，容易给用户选择分面带来困难。为了将探索式的检索方式运用于水利元数据搜索领域，针对水利元数据分面过多的问题，提出了一种基于保持率的分面推荐算法，设计和实现了水利元数据的动态分面搜索引擎。实验结果表明，所提出的算法能够有效地提高用户的检索效率。

英文摘要：

Aiming at the problem that sharing of lots of water conservancy metadata needs to build a search engine, since the defects of knowledge in the field of water conservancy metadata for ordinary users, it is necessary to introduce an exploratory access technology for users to express retrieval requests exactly to realize the function of metadata retrieval. Faceted search is an exploratory way of retrieval. According to the multi-dimensional attributes of the objects, the system clusters the search results, therefore users can choose facet values to filter them. With the increase of water conservancy metadata and the isomerization of the metadata,the number of facets is also increas- ing. If all the facets are displayed to users, it is difficult for them to select facets. In order to use exploratory ways of retrieval in the field of water conservancy metadata searching, aiming at the problem of too many facets of water conservancy metadata, a faceted recommen- dation algorithm based on retention rate is proposed, and the dynamic faceted search engine of water conservancy metadata is designed and implemented. Experimental results show that it can efficiently improve the retrieval efficiency of users.