At present,most studies use some dimensionality reduction methods to convert high-dimensional vectors into low-dimen-sional vector representations,and then apply related vector retrieval optimization technology to achieve fast similarity retrieval,thereby improving the application performance of large models.Currently,there are many and scattered dimensionality reduction methods for high-dimensional data,and the dimensionality reduction methods used in different research backgrounds are different.Similarly,there are also many different retrieval ideas and optimization methods in vector retrieval technology.By reviewing the main ideas and optimization methods of recent dimensionality reduction and retrieval algorithms,this paper helps to generate inspir-ing connections between the two and support the development and in-depth research of subsequent high-dimensional vector retrieval optimization algorithms.
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