Fast similarity search methods for large-scale and high-dimensional data sets by using complex networks

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This research project proposed a similarity search method that utilized a degree-reduced k-nearest neighbor graph (k-DR graph), which is a small-world network (or graph) in complex networks, for a search index structure, and that explored the k-DR graph by a greedy search or a best-first search algorithm. We have experimentally confirmed that this similarity search method was applicable to a variety of media types such as documents, images, and speech signals (utterances) and quickly found objects similar to a given query. The proposed similarity method with the foregoing properties is expected to serve as a base for novel similarity search techniques.