Kollios et al., 2003 - Google Patents
Efficient biased sampling for approximate clustering and outlier detection in large data setsKollios et al., 2003
- Document ID
- 3907373337308390404
- Author
- Kollios G
- Gunopulos D
- Koudas N
- Berchtold S
- Publication year
- Publication venue
- IEEE Transactions on knowledge and data engineering
External Links
Snippet
We investigate the use of biased sampling according to the density of the data set to speed up the operation of general data mining tasks, such as clustering and outlier detection in large multidimensional data sets. In density-biased sampling, the probability that a given …
- 238000005070 sampling 0 title abstract description 185
Classifications
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- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30386—Retrieval requests
- G06F17/30424—Query processing
- G06F17/30533—Other types of queries
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- G—PHYSICS
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- G06F17/30486—Unary operations; data partitioning operations
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- G06F17/30587—Details of specialised database models
- G06F17/30592—Multi-dimensional databases and data warehouses, e.g. MOLAP, ROLAP
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- G—PHYSICS
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- G06F17/3071—Clustering or classification including class or cluster creation or modification
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
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- G06F17/30946—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type indexing structures
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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