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Novel multi-source data fuzzy clustering algorithm

A fuzzy clustering method and multi-source data technology, applied in the field of multi-source data fuzzy clustering

Inactive Publication Date: 2016-11-16
BEIJING JIAOTONG UNIV +2
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  • Abstract
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  • Claims
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Problems solved by technology

[0009] Currently, there is no scheme to effectively apply clustering algorithms to multi-source learning research

Method used

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  • Novel multi-source data fuzzy clustering algorithm
  • Novel multi-source data fuzzy clustering algorithm

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Embodiment Construction

[0031] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0032] Those skilled in the art will understand that unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the word "comprising" used in the description of the present invention refers to the presence of said features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, Integers, steps, operations, elements, components, and / or groups thereof. It will be understoo...

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Abstract

The invention provides a novel multi-source data fuzzy clustering algorithm which mainly comprises the following steps: multi-source data is collected, each source in the multi-source data includes a plurality of categories, each category comprises a plurality of dimensions, an object function of a multi-source data fuzzy clustering method for the multi-source data is built, each source in the multi-source data is weighted in the object function, different dimensions in different categories of sources in the multi-source data are weighted, parameters in the object function are initialized, a clustering center and parameters of the object function are subjected to repetitive updating and clustering operation, and multi-source data clustering processes can be finished. According to the novel multi-source data fuzzy clustering algorithm, correlation of multiple sources in the multi-source data and difference in contribution made by different characteristics to different category identification are used, and therefore a novel clustering algorithm which combines different vision angle weighting and different weights of different characteristics is constructed; the novel multi-source data clustering algorithm disclosed in the invention is better than other multi-source data clustering algorithms in explanatory property and reliability of clustering results.

Description

technical field [0001] The invention relates to the technical field of multi-source data analysis, in particular to a multi-source data fuzzy clustering method. Background technique [0002] With the increasing ability of people to collect, store, transmit and manage data, various industries have collected and accumulated a large amount of data resources from various channels / channels. For example, "Nature" published a special issue of big data in September 2008, listing that in bioinformatics, transportation, finance, Internet and other fields, multi-source data has played an increasingly important role in scientific research. One of the characteristics of such big data is hybridity, which requires special attention when intelligent data processing of such big data. [0003] The complexity of data is very related to the source of data collection. It is precisely because the actual application data comes from multiple channels that the description of complex objects and com...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2321
Inventor 于剑刘烨詹德川
Owner BEIJING JIAOTONG UNIV
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