关系数据库数据社区的检索方法研究

发布时间：2018-04-10 13:45

本文选题：关系数据库 + 数据图　；参考：《大连海事大学》2013年硕士论文

【摘要】：如今互联网快速发展,关键字搜索技术为网页搜索等方面提供了关键技术支持,这是如今网页搜索获得巨大成功的关键,使得用户可以用简单的自己熟知的关键字在网上寻找自己需要的信息。在众多的数据库中,关系数据库是当前最为流行的、使用最多的一种,只要用户掌握一定的结构化查询语言和数据库的基本模式知识就能够进行操作。但是,如今绝大多数网民并不具备这些专业化知识,如何让关系数据库能够支持高效的关键字检索成为近来的研究热点,因为关系数据库的关键字检索可以使用户摆脱结构化查询语句(如SQL等)的束缚。关系数据库关键字搜索与网络搜索引擎工作相比又有其不同特点,比如：数据库由元组组成,元组间有键值或语意关系等。关键字检索作用于关系数据库上使检索得到的结果再进行一定程度的信息整合,得到用户真正需要的信息。本文提出的关系数据库数据社区检索方法是以中心节点为驱动及其所能够到达各关键字节点的组合来确定一个社区的方法。本篇社区由节点和边组成,节点又分三类：关键字节点、中心节点和路径节点；边可以是无向边也可以是有向边。把各关键字向外扩展一定的距离所能够到达的公共节点设立为中心节点,中心节点结构中有它所能够到达的各关键字节点的信息,以此来判断能否满足社区的形成条件,也就是用户想得到的信息。对于排序问题,利用中心节点到达各关键字节点的开销为依据进行相应的规范调整,以便得到最优结果。本文设计了数据社区检索方法框架,并实现了相关算法。以DBLP数据集对该算法进行了验证,其结果证实了算法思想的可行性和具体算法的高效性。本文检索方法的思想也可以扩展到其他的领域。与传统的关系数据库关键字检索结果相比,本算法有效地改善了单个结果包含信息量少、各结果间缺少相应的依赖联系等问题,通过本文的算法实现使得单个结果包含了较为丰富的信息也使得用户更清晰、明了的理解检索结果间的关系。
[Abstract]:Now the rapid development of the Internet, the keyword search technology provides key technical support for web search, which is now the key of web search to achieve great success, so that users can use their own familiar simple keyword search for the information they need on the Internet. In many databases, relational database is the most popular use. One of the most, as long as the users master some knowledge of basic mode of structured query language and database to operate. But now, the vast majority of users do not have these specialized knowledge, how to make the relational database can support efficient keyword search has become the focus of research recently, because relational database keyword search allows the user to get rid of structured the query (such as SQL) bound.
Relational database keyword search compared with network search engines has different characteristics, such as: the database consists of tuples, key or semantic relations between tuples. Such as keyword search in relational database on the retrieval results and information integration to a certain extent, get the needed information for users.
In this paper the relational database community retrieval method is based on the center node as the combination of drive and can reach each keyword nodes to determine a community. The community composed of nodes and edges, nodes are divided into three categories: keyword node, the central node and the path node; the edge can be undirected edges can be directed edges. The key expansion common node distance can reach the set for the central node, with each keyword nodes it can reach the information center node structure, in order to determine whether it can meet the condition of the formation of a community, also is the information the user wants. For the sorting problem, use the central node to each keyword node overhead as the basis for the corresponding standard adjustment, in order to get the optimal results.
This paper introduces the design of data retrieval community framework, and implement the relevant algorithm. Based on DBLP data set to validate the algorithm, and the result confirms that the efficiency of the algorithm feasibility and specific algorithm. The retrieval method thought in this paper can also be extended to other areas. And the relational database keyword search results compared to traditional. This algorithm can effectively improve the individual results contain less information, the lack of corresponding relationship between the results and other issues, through this algorithm makes the single result contain abundant information makes users more clear, the relationship between the clear understanding of the retrieval results.

【学位授予单位】：大连海事大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP311.132.3

【共引文献】