Linear matching method of database index files based on discrete mathematics
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ORIGINAL RESEARCH
Linear matching method of database index files based on discrete mathematics Li Wei1 · Hui Xie1 Received: 19 June 2020 / Accepted: 27 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract A linear matching method for database index files based on discrete mathematics is proposed. Firstly, the relaxation clustering algorithm is adaptively improved. The corresponding Gauss kernel parameters are obtained by using the domain information of data points direction of the cluster load. The cluster minimal circumscribed matrix is set up according to the calculated coordinate component value, and the optimal cluster is obtained. Electronic dictionary is used to calculate the semantic association between tags of index files after clustering to obtain the name similarity, the cardinal similarity is obtained according to the cardinal constraints, the context similarity is calculated through the path between leaf node and root node, the matched descendant node is queried by the neighbor of non-leaf node, and the descendant node is queried. The number of leaf nodes and their similarity to the original node are calculated for different paths to complete the matching of database index files. The experimental results show that the average energy consumption of matching index files is 439 J and the matching accuracy is 99.72%. Keywords Discrete mathematics · Database · Index file · Linear matching · Clustering
1 Introduction Users of dBASE, Foxplus and Foxpro will not be unfamiliar with the index files of the database. As long as the index on to [for ] statement is executed on the currently open database, an index with the extension of IDX can be established (Yang 2018). The index file is established according to the record information of the database. Once the database is indexed, when both the database and the index are opened at the same time, using find or seek can quickly locate the existence of the searched string record and locate the database record pointer at the record place (Years 2018). Find or Seek can refer to the relevant index files through the operation of the index files, but the indexing effect of the index files through the above process is poor. Index file in database * Hui Xie [email protected] Li Wei [email protected] 1
School of Software and Communication Engineering, Xiangnan University, Chenzhou, China
is a dense index like B + tree. Index file in database is mainly designed for quick retrieval (Li et al. 2017). Besides normal use, index file can be used to achieve some purpose or replace some commands to simplify programming or shorten execution time. However, if used improperly, it may cause problems. The questions become more complicated. Therefore, it is necessary to match the index files in the database by corresponding methods. When searching the database by index keyword string in high-level language, the index precision and index efficiency will be improved (Zhang 2017). Through investigation and analysis, it is found that there are many methods to
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