CORDIS Project
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This project focuses on enhancing similarity search methods in large and complex data sets. By developing new theoretical foundations and practical techniques, it aims to improve the efficiency and reliability of identifying similar items in various applications such as machine learning and information retrieval.
Similarity search is the task of identifying, in a collection of items, the ones that are “similar” to a givenquery item.
This task has a range of important applications (e.g. in information retrieval, patternrecognition, statistics, and machine learning) where data sets are often big, high dimensional, andpossibly noisy.
State-of-the-art methods for similarity search offer only weak guarantees when faced withbig data.
Either the space overhead is excessive (1000s of times larger than the space…
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