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Louhi et al., 2016 - Google Patents

Incremental nearest neighborhood graph for data stream clustering

Louhi et al., 2016

Document ID
6522502679386609493
Author
Louhi I
Boudjeloud-Assala L
Tamisier T
Publication year
Publication venue
2016 International Joint Conference on Neural Networks (IJCNN)

External Links

Snippet

In this paper we deal with one of the most relevant problems in the field of data mining, the real time processing and visualization of data streams. To deal with data streams we propose a novel approach that uses a neighborhood-based clustering. Instead of …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

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    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6218Clustering techniques
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    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
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    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6251Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on a criterion of topology preservation, e.g. multidimensional scaling, self-organising maps
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
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    • G06F17/3061Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30705Clustering or classification
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    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
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    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
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    • G06N5/02Knowledge representation
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    • G06Q10/00Administration; Management

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