基于IRST的谱图相似性查找方法研究

The research of spectrogram similarity search method based on IRST

光谱图相似性匹配是推测化合物结构的重要研究方法之一,而如何在标准谱图数据库中进行相似性查找是关键步骤。传统的谱图匹配方法在数据量较大时,检索效率较低。本文首次将互关联后继树(TRST)算法思想应用于光谱图数据领域,从光谱图特征数据点出发,通过对算法的改进,提出了1种基于斜率序列的互关联后继树算法(SSIRST)实现光谱图相似性匹配查找,旨在通过减少匹配过程中的数据量缩短查找时间。实验结果表明,算法可以有效提高光谱图相似性匹配查找效率1倍以上。

Spectrogram similarity matching is one of the important research methods of inferring chemical compound structure, similarity search in standard spectrogram database is the key step of research. The retrieval efficiency is low when use traditional spectrogram matching method in large data amount. This is the first time that the paper use the idea of Inter-Relevant Successive Trees（IRST） algorithm, starting from the spectrum characteristic of data points, improve this algorithm, Put forward a algorithm of Inter-Relevant Successive Trees based on slope sequence（SSIRST）, Aims to reduce the amount of data in the matching process to shorten the search time. According to the simulation results, the result demonstrates： This algorithm can effectively improve the efficiency of spectrogram search more than one times.