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Data fusion method based on FCM algorithm

A technology of data fusion and algorithm, applied in the field of data fusion based on FCM algorithm, can solve problems such as insufficient accuracy of user feature acquisition, complex data types, low fusion efficiency, etc., and achieve the effect of improving effective utilization and user satisfaction

Inactive Publication Date: 2020-04-10
HANGZHOU SUNYARD DIGITAL SCI
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Problems solved by technology

[0006] The invention provides a data fusion method based on the FCM algorithm, which can effectively solve the problems of low fusion efficiency and insufficient accuracy of user feature acquisition caused by high-dimensional data sets with complex data types and numerous data features

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  • Data fusion method based on FCM algorithm

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Embodiment Construction

[0028] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0029] A data fusion method based on the FCM algorithm, such as figure 1 shown, including the following steps:

[0030] S1: Collect historical data of heterogeneous and multi-source cross-border big data, including three major aspects: internal system data, Internet data, and external data from regulatory authorities in related fields.

[0031] S2: Preprocessing the above data.

[0032] S3: Determine whether the preprocessed data is less than 3-dimensional, and use the t-SNE algorithm to directly reduce the dimension for data with a dimension less than 3; for high-dimensional big data with a dimension greater than or equal to 3, first use the PCA algorithm for the first dimensionality reduction, so that It is reduced to 2 dimensions, and then the t-SNE algorithm is used for the second dimensionality reduction on the data after the first dimensionalit...

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Abstract

The invention discloses a data fusion method based on FCM algorithm. The method comprises the following steps: S1, collecting an original data set of heterogeneous multi-source cross-boundary big data; S2, performing data preprocessing on the collected original data set; S3, performing data dimension reduction on the preprocessed data; S4, performing fuzzy clustering on the data subjected to dimension reduction by utilizing FCM algorithm to extract feature keywords; A5, calculating the weights of the feature keywords and the similarity between the different feature keywords through TF-IDF technology, and constructing a weight and similarity matrix; and S6, preferentially fusing the data with high similarity and large weight. According to the method, effective fusion of multi-source heterogeneous high-dimensional data is realized, the problems of low fusion efficiency and insufficient user feature acquisition accuracy caused by a high-dimensional data set with complex data types and numerous data features are solved, and the effective utilization rate of data and the user satisfaction of enterprises are improved.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a data fusion method based on an FCM algorithm. Background technique [0002] With the advent of the era of big data, among the large amount of data with complex structures left by users, the amount of data that enterprises can obtain is huge and redundant, which makes it impossible for enterprises to provide personalized services according to user preferences. Therefore, when different analysis techniques are fused together for comprehensive data fusion analysis, the key to fusion is to combine these sources of information to provide joint analysis of multidimensional big data. [0003] At present, data fusion technology is mainly divided into from low to high according to the level of fusion: fusion based on pixel level, fusion based on feature level and fusion based on decision level. However, there are currently few comprehensive fusion methods involving complex structured dat...

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Application Information

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IPC IPC(8): G06F16/28G06N20/00
CPCG06F16/283G06F16/285G06N20/00
Inventor 汪继锋颜炎韦昆
Owner HANGZHOU SUNYARD DIGITAL SCI
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