Searching in high-dimensional spaces
نویسندگان
چکیده
منابع مشابه
Searching in High-Dimensional Metric Spaces using BP-Trees
Similarity search in high-dimensional metric spaces is a key operation in many applications, such as multimedia databases, image retrieval, object recognition, and others. The high dimensionality of the data requires special index structures to facilitate the search. A problem regarding the creation of suitable index structures for high-dimensional data is the relationship between the geometry ...
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As databases increasingly integrate different types of information such as time-series, multimedia and scientific data, it becomes necessary to support efficient retrieval of multi-dimensional data. Both the dimensionality and the amount of data that needs to be processed are increasing rapidly. As a result of the scale and high dimensional nature, the traditional techniques have proven inadequ...
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In this paper we introduce a new paradigm for similarity search, called PAC-NN (probably approximately correct nearest neighbor) queries, aiming to break the “dimensionality curse” which inhibits current approaches to be applied in high-dimensional spaces. PAC-NN queries return, with probability at least 1− δ, a (1+ )-approximate NN – an object whose distance from the query q is less than (1 + ...
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Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usually very high dimensional. Unfortunately, no proximity search algorithm does well in high dimensions. An alternative to overcome this problem is the use of approximate and probabilistic algorithms, which trade time for accuracy....
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Data mining applications usually encounter high dimensional data spaces. Most of these dimensions contain ‘uninteresting’ data, which would not only be of little value in terms of discovery of any rules or patterns, but have been shown to mislead some classification algorithms. Since, the computational effort increases very significantly (usually exponentially) in the presence of a large number...
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ژورنال
عنوان ژورنال: ACM Computing Surveys
سال: 2001
ISSN: 0360-0300,1557-7341
DOI: 10.1145/502807.502809