DISTRIBUTED INDEX DATA STRUCTURE
First Claim
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1. A method for use in forming a computer generated distributed index data structure, wherein said distributed index data structure is distributed among a set of two or more processors, the method comprising:
- determining two or more global cluster centers based at least in part on at least a portion of a set of data objects distributed to two or more processors;
determining two or more global pivots based at least in part on at least a portion of said set of data objects distributed to two or more processors;
associating one or more data objects with a given cluster center of said two or more global cluster centers, wherein said given cluster center may be associated based at least in part on a closeness determination between said one or more data objects and said two or more global cluster centers; and
determining a table containing distances between one or more of said global pivots and said data objects associated with said given global cluster center.
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Abstract
The subject matter disclosed herein relates to forming a computer generated distributed index data structure.
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Citations
20 Claims
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1. A method for use in forming a computer generated distributed index data structure, wherein said distributed index data structure is distributed among a set of two or more processors, the method comprising:
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determining two or more global cluster centers based at least in part on at least a portion of a set of data objects distributed to two or more processors; determining two or more global pivots based at least in part on at least a portion of said set of data objects distributed to two or more processors; associating one or more data objects with a given cluster center of said two or more global cluster centers, wherein said given cluster center may be associated based at least in part on a closeness determination between said one or more data objects and said two or more global cluster centers; and determining a table containing distances between one or more of said global pivots and said data objects associated with said given global cluster center. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. An article comprising:
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a computer-readable medium comprising computer-readable instructions stored thereon, which, if executed by one or more processors, operatively enable a computing platform to; form a computer generated distributed index data structure, wherein said distributed index data structure is distributed among a set of two or more processors, comprising; determine two or more global cluster centers based at least in part on at least a portion of a set of data objects distributed to two or more processors; determine two or more global pivots based at least in part on at least a portion of said set of data objects distributed to two or more processors; associate one or more data objects with a given cluster center of said two or more global cluster centers, wherein said given cluster center may be associated based at least in part on a closeness determination between said one or more data objects and said two or more global cluster centers; and determine a table containing distances between one or more of said global pivots and said data objects associated with said given global cluster center. - View Dependent Claims (14, 15, 16)
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17. An apparatus comprising:
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a computing environment system, said computing environment system being operatively enabled to; form a computer generated distributed index data structure, wherein said distributed index data structure is distributed among a set of two or more processors, comprising; determine two or more global cluster centers based at least in part on at least a portion of a set of data objects distributed to two or, more processors; determine two or more global pivots-based at least in part on at least a portion of said set of data objects distributed to two or more processors; associate one or more data objects with a given cluster center of said two or more global cluster centers, wherein said given cluster center may be associated based at least in part on a closeness determination between said one or more data objects and said two or more global cluster centers; and determine a table containing distances between one or more of said global pivots and said data objects associated with said given global cluster center. - View Dependent Claims (18, 19, 20)
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Specification