基于Lucene的石墨烯中文文献搜索引擎设计与实现

Design and Implementation of Graphene Chinese Literature Search Engine Based on Lucene

近年来,材料领域对于石墨烯的探索越来越深入,与此同时,大量的专业文献被发表在各类期刊、会议中。在大量文献中查找所需要的文献也变得越来越困难。传统数据库搜索效率低下且搜索结果并不尽如人意。因此,本文设计了一种基于Lucene工具包,Python爬虫技术等开发的一套本地全文检索系统。首先利用爬虫技术获取互联网上相关文献资料,接着保存到MySQL数据库中,通过自定义开发Lucene创建索引和搜索服务,从而完成一整套搜索引擎系统服务。经大量测试表明,该系统搜索结果准确率接近数据库搜索,搜索速度也远快于传统的数据库查询。因此,该系统可以用于进行石墨烯中文文献的搜索查询,从而提高科研人员查阅文献的效率。

In recent years, the exploration of graphene in the field of materials has become more and more in-depth, and at the same time, a large number of professional literatures have been published in various journals and conferences. Finding the required literature in a large body of literature has also become increasingly difficult. Traditional database searches are inefficient and search results are not as satisfactory. Therefore, this paper designs a local full-text retrieval system based on Lucene toolkit, Python crawler technology and so on. Firstly, the crawler technology is used to obtain relevant documents on the Internet, and then saved to the MySQL database to create a complete set of search engine system services by customizing Lucene to create an index and search service. A large number of tests have shown that the accuracy of the search results of the system is much higher than that of the database search, and the search speed is much faster than the traditional database query. Therefore, the system can be used for searching and querying graphene Chinese literature, thereby improving the efficiency of researchers in accessing documents.