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Consistency expression method for multi-source heterogeneous big data

A multi-source heterogeneous data and multi-source heterogeneous technology, applied in the information field, can solve problems such as inability to adapt to the characteristics of multi-source data

Inactive Publication Date: 2016-08-24
INST OF INFORMATION ENG CAS
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AI Technical Summary

Problems solved by technology

Traditional single-source learning methods can no longer adapt to the characteristics of multi-source data

Method used

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  • Consistency expression method for multi-source heterogeneous big data
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Embodiment Construction

[0082] In order to make the above objects, features and advantages of the present invention more obvious and understandable, the present invention will be further described below through specific embodiments and accompanying drawings.

[0083] The consistent representation method of multi-source heterogeneous big data provided by the present invention is composed of isomorphic correlation redundant transformation IRRT and correlation-based joint feature learning CJFL algorithm, and the gradual optimization of the model is realized through a cyclic iteration process.

[0084] The IRRT model in formula (4) can be simplified as:

[0085]

[0086] in, is a smooth objective function, Z=[A Z B Z ] symbolizes the optimization variable, while is a closed convex set, which is defined as:

[0087]

[0088] Since f( ) is a continuously differentiable function with Lipschitz continuous gradient L (reference: Y.Nesterov.Introductorylectures on convex optimization, volume 87.Sp...

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Abstract

The invention discloses a consistency expression method for multi-source heterogeneous big data. In the method, given the characteristic heterogeneity of multi-source heterogeneous data, the multi-source heterogeneous data is projected to a middle-layer redundant feature homogeneous space by use of the semantic complementarity of the multi-source heterogeneous data and based on a subspace learning method; and related descriptions from different sources are coupled together in the homogeneous space. In order to excavate the semantic consistency of homogeneous descriptions in the middle-layer space, the characteristic homogeneous descriptions are projected to a high-layer semantic sharing subspace by use of the priori knowledge so as to eliminate the redundancy and noise information; and a sematic-consistent mode of the multi-source heterogeneous data can be obtained. The method disclosed by the invention is conducive to obtaining an accurate and robust multi-source data evaluation analysis result in the fields such as multimedia analysis, information retrieval and medical diagnosis.

Description

technical field [0001] The invention belongs to the field of information technology, and aims at the problem of feature heterogeneity in a massive multi-source heterogeneous data environment, and proposes a consistent representation method for multi-source heterogeneous big data. Background technique [0002] In recent years, with the emergence of a large number of high-tech digital products, the multi-source heterogeneous data (Multi-source Heterogeneous Data) generated by these heterogeneous electronic devices has spread to every corner of people's real life. The so-called multi-source heterogeneous data refers to data that comes from different sources or channels, but expresses similar content, and appears in various styles such as different forms, different sources, different perspectives, and different backgrounds. Such as figure 1 As shown, Sina Weibo, Tencent WeChat and Sohu websites report different forms of the same news; the brains of Alzheimer's patients can be p...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06F17/27
CPCG06F16/215G06F16/217G06F40/30
Inventor 张磊王树鹏云晓春
Owner INST OF INFORMATION ENG CAS
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