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Automobile sale prediction method considering brand emotions

A forecasting method and brand technology, applied in forecasting, marketing, instruments, etc., can solve problems such as low forecasting accuracy

Inactive Publication Date: 2017-07-14
HEFEI UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing research lacks consideration of the seasonal trend of car sales, which leads to low prediction accuracy.

Method used

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  • Automobile sale prediction method considering brand emotions
  • Automobile sale prediction method considering brand emotions
  • Automobile sale prediction method considering brand emotions

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0049] In this example, if figure 1 As shown, a car sales forecast method considering brand emotion follows the following steps:

[0050] Step 1. Collect the review data of all the cars owned by the car brand b purchased by consumers in the month t, which is denoted as Indicates the kth comment data of month t, taking "Car Home" as an example, a typical comment data such as figure 2 Shown, and the kth comment data of the tth month Including: the kth scoring data of the tth month Such as figure 2 As shown in area A, and the kth comment text data of the tth month Such as figure 2 shown in area B; and Indicates the kth scoring data of the tth month The i-th scoring item of , such as figure 2 Area A includes space, power, handling, fuel consumption, comfort, appearance, interior and cost-effective 8 scoring items in turn; Represents the kth comment text data of the tth month The jth comment text of , such as figure 2 Area B includes space, power, hand...

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Abstract

The invention discloses an automobile sale prediction method considering brand emotions. The method comprises the steps that 1, comment data of automobiles purchased by consumers is collected; 2, an emotional dictionary construction method based on pointwise mutual information is proposed, and emotional values of all emotional words in the comment data are obtained; 3, the emotions in the comment text data are quantized based on an emotional dictionary, and the emotions are further collected to obtain an emotional value of an automobile brand; 4, an automobile monthly sale prediction model of brand granularity is constructed; 5, an objective function of the automobile brand sale prediction model is defined; and 6, a grid search method is utilized to solve the objection function to obtain an optimal parameter value, and therefore the prediction model is utilized to predict the sale of the next month. Through the method, seasonal variation of a sale time sequence and a short-term prediction ability of public praise emotional tendency factors of the consumers in network big data can be fully mined, therefore, automobile sale prediction is refined to more microcosmic brand granularity, and predication precision is improved.

Description

technical field [0001] The invention belongs to the field of sales forecasting, in particular to an automobile sales forecasting method for predicting monthly sales of various automobile brands and considering brand emotion. Background technique [0002] China's auto industry has achieved rapid development in the past few decades, and has become one of the leading industries supporting and stimulating the sustained and rapid growth of China's economy. In the face of the current complex domestic and foreign economic environment and increasing downward pressure on the economy, accurate forecasting of automobile sales is not only for policy makers who control the development and growth of the automobile market from a macro perspective, but also to researching the market from a micro perspective. Car manufacturers who analyze market conditions and formulate marketing strategies all play an extremely important role. [0003] The existing automobile sales forecasting methods main...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06F17/27G06Q10/04G06Q30/02
CPCG06F16/35G06F16/374G06F40/216G06Q10/04G06Q30/0202
Inventor 章旭刘业政王锦坤
Owner HEFEI UNIV OF TECH
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