Big data classification rule optimization method and device

An optimization method and big data technology, applied in database models, relational databases, electronic digital data processing, etc., can solve the problem of lack of effective reuse and improvement of rule customization, improve application versatility and model tolerance, reduce The effect of time cost and labor cost

Inactive Publication Date: 2019-08-06
北京中科智营科技发展有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In view of the above problems, the embodiments of the present invention provide a method and device for optimizing big data ...

Method used

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  • Big data classification rule optimization method and device
  • Big data classification rule optimization method and device
  • Big data classification rule optimization method and device

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0091] ("e-commerce", "e-commerce", "wechat business") / / with "e-commerce", "e-commerce", "wechat business" as the classification keywords, the weight coefficient in the classification results is 1.0

[0092] [0.5] ("Shop","B2B","O2O") / / Take "Shop","B2B","O2O" as the classification keywords, and the weight coefficient in the classification results is 0.5>

example 2

[0094]

[0095] The big data classification rule optimization method of the embodiment of the present invention establishes a basic data structure according to keywords and their topology, adapts the data structure to the type of rule parameters, and improves the readability of the data structure through keywords.

[0096] The process of establishing a rule set in the method for optimizing big data classification rules in an embodiment of the present invention is as follows: image 3 shown. exist image 3 In , the process of establishing a rule set includes:

[0097] Step 121: Establish a rule set keyword.

[0098] Step 122: Create a rule set subset of the rule set and corresponding subset keywords.

[0099] Step 123: Establish a scene set and corresponding scene keywords of the rule set subset.

[0100] Step 124: Establish a keyword topology structure according to the rule set keywords, subset keywords or scene keywords.

[0101] Step 125: Add a rule...

example 3

[0208]

[0209]

[0210] Step 216: Store the associated data of classification categories according to the storage topology and storage fields.

[0211] The associated data may be descriptive data of the classification category, such as feature data of the classification category, or may be associated data of the classification category, such as rule data of the classification category.

[0212] The classification optimization method for data presentation in the embodiment of the present invention establishes a classification data structure and new field data classification category framework with better versatility for similar data fields, so that classification categories have a common data processing basis for reuse, reuse and rapid update.

[0213] Such as Figure 8 As shown, in an embodiment of the present invention, the process of establishing a classification category includes:

[0214] Step 221: Register the classification identifier through the...

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Abstract

The invention provides a big data classification rule optimization method and device, and solves the technical problem that an existing rule customization process is lack of effective multiplexing andimprovement. The method comprises the steps of establishing a data structure of storage rules; forming a rule set for determining a theme through the data structure; and performing scene classification on the source data according to the rule set. A complete topological structure of theme classification and scene classification is formed by utilizing a data structure; parameters of different classification processes are configured in order; the complex parameter reference process of the big data classification model forms a structured classification system; classification iteration parameterdata, key enumeration data and classification process threshold adjustment intervals in the classification model can be effectively managed and reasonably configured; therefore, the big data classification model has a technical means for moderately adjusting the characteristic change of the source data, frequent adjustment of a training set and a learning process for evolution of an objective scene of a source data forming process is avoided, and the time cost and the labor cost of big data classification are reduced.

Description

technical field [0001] The invention relates to the technical field of data classification, in particular to a method and device for optimizing big data classification rules. Background technique [0002] In the prior art, big data classification is to obtain similar features between data through effective data classification methods, divide data into different categories according to similar features, and perform further feature processing according to categories. In the data classification method, the self-learning classification method is limited by the training set, and the classification model formed is positively related to the big data industry field, and the classification model is not universal. At the same time, limited by the labor cost and training time cost of the training set data of the classification model, it can only achieve efficient processing of fixed classification categories for flexible data classification scenarios, and cannot make timely adjustments...

Claims

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Application Information

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IPC IPC(8): G06F16/2455G06F16/28
CPCG06F16/24564G06F16/285
Inventor 黄浩
Owner 北京中科智营科技发展有限公司
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