Applications such as audio fingerprinting require search in high dimensions: find an item in a database that is similar to a query. An important property of this search task is that negative answers are very frequent: much of the time, a query does not correspond to any database item. This paper proposes Redundant Bit Vectors (RBVs): a novel method for quickly solving this search problem. RBVs rely on three key ideas: approximate the high-dimensional regions/distributions as tightened hyperrectangles, partition the query space to store each item redundantly in an index and use bit vectors to store and search the index efficiently.
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