SiLi Index: Data Structure for Fast Vector Space Searching

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Year of publication 2019
Type Article in Proceedings
Conference Proceedings of the Thirteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2019
MU Faculty or unit

Faculty of Informatics

Keywords word embeddings; vector space; semantic similarity
Description Nearest neighbor queries in high-dimensional spaces are ex-pensive. In this article, we propose a method of building and querying astand-alone data structure, SiLi (SimilarityList) Index, which supports ap-proximating the results of k-NN queries in high-dimensional spaces, whileusing a significantly reduced amount of system memory and processortime compared to the usual brute-force search methods.
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