基于元数据的搜索引擎的设计与实现

Design and Implementation of Meta Search Based Search Engine

针对物流元社区共享过程需要构建搜索引擎,对于普通用户来说,对物流元数据领域的相关认识还存在一定的缺陷,需要引入探索式访问技术,进一步表达检索请求,可实现元数据的检索功能,分面检索是一种探索检索方式,能够根据物体多维系最终完成检索结果聚类分析,因此用户可以选择分面值完成结果筛选。随着目前物流元数据增加以及异构化程度提升,分面数量逐渐增加,如果将所有分面均展示给用户则很容易导致用户出现选择困难。为将探索检索方式应用于物流元数据检索过程中,在本研究中针对物流元数据分面较多的问题,提出了基于保持率的分面推荐算法,并设计和实现物流元数据动态分面搜索引擎,通过研究结果发现所提出的算法能够显著提升最终的检索效率。

For the sharing process of logistics meta-community,it is necessary to build a search engine.For ordinary users,there is still some defects in the knowledge of logistics metadata.It is necessary to introduce exploratory access technology to further express retrieval requests and realize metadata retrieval.Function,faceted search is a kind of exploration and retrieval method,which can finally complete the clustering analysis of search results according to the object multi-dimensional system,so the user can select the facet value to complete the result screening.As the current logistics metadata increases and the degree of isomerization increases,the number of facets gradually increases.If all the facets are displayed to the user,it is easy to cause the user to have difficulty in selecting.In order to apply the exploration and retrieval method to the process of logistics metadata retrieval,in this study,based on the problem of more facet of logistics metadata,a maintenance-based faceted recommendation algorithm was proposed,and a dynamic faceted search of logistics metadata was designed and implemented.The engine,through the research results,found that the proposed algorithm can significantly improve the final retrieval efficiency.