关系数据库中关键词搜索算法的研究

发布时间：2018-03-12 06:20

本文选题：关系数据库　切入点：信息检索　出处：《黑龙江大学》2013年硕士论文　论文类型：学位论文

【摘要】：关系数据库中的关键词搜索问题已经逐渐成为信息检索领域的研究热点。由于基于关系数据库的关键词搜索技术不需要用户具有任何SQL语法知识和数据库模式知识，只需要输入关键词，便可以像互联网搜索引擎一样方便的进行关键词搜素，因此赢得了许多用户的青睐。本文对关系数据库中的关键词搜索问题做了相关研究，对关键词搜索算法进行了改进与创新，主要研究成果及贡献如下：对基于模式图的关系数据库关键词搜索问题进行了研究，在现有的基于模式图的关键词搜索框架内，通过提出新的编码规则和迭代算法对关键词搜索算法进行了改进。通过一系列实验表明，该算法搜索结果重复率较低，在数据量较小时，算法效率较高。对基于数据图的关系数据库关键词搜索问题进行了研究，，提出了一种基于分类Steiner树和集合连接的关键词搜索算法，通过分类Steiner树降低了搜索结果的平局率。实验结果表明，该算法的优势在于第一条结果返回给用户的时间较短，可以大大减少用户等待的时间。在数据量适中时，该算法的效率较高。将模式图与数据图相结合来解决关键词搜索问题也是本文研究的问题之一。本文提出了一套体系结构完整的关键词搜索系统，并且首次提出了同表查询问题。实验结果表明，基于模式图与数据图相结合的关键词搜索算法在数据量较大时，算法效率较高。
[Abstract]:Keyword search in relational database has gradually become a hot topic in the field of information retrieval. Because the key word search technology based on relational database does not require users to have any knowledge of SQL syntax and database schema. Just input keywords, you can search keywords as easily as the Internet search engine, so it has won the favor of many users. In this paper, we do some research on keyword search in relational database. The keyword search algorithm is improved and innovated. The main research results and contributions are as follows:. In this paper, the key word search problem of relational database based on schema graph is studied. In the existing framework of keyword search based on schema graph, A series of experiments show that the search result repetition rate of the algorithm is low and the efficiency of the algorithm is high when the amount of data is small. In this paper, the key word search problem of relational database based on data graph is studied, and a keyword search algorithm based on classified Steiner tree and set connection is proposed. By classifying Steiner tree, the tie rate of search results is reduced. The experimental results show that, The advantage of the algorithm is that the first result can be returned to the user in a short time, which can greatly reduce the waiting time of the user. When the amount of data is moderate, the efficiency of the algorithm is higher. It is also one of the problems in this paper to solve the keyword search problem by combining schema graph with data graph. In this paper, a complete system of keyword search is proposed, and the query problem of the same table is proposed for the first time. The experimental results show that, The keyword search algorithm based on the combination of schema graph and data graph is more efficient when the amount of data is large.
【学位授予单位】：黑龙江大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP311.13;TP391.3

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