Automobile competitive product comparison method based on viewpoint mining analysis

An opinion mining and automotive technology, applied in the field of natural language processing opinion mining and analysis, can solve problems such as long-term dependence, and achieve the effects of improved accuracy, good general ability, robustness, and strong subjectivity

Pending Publication Date: 2019-11-05
SOUTHWEST JIAOTONG UNIV
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Problems solved by technology

But the disadvantage is that there is a problem of long-term dependence. Using the self-attention mechanism allows the decoder to use the final hidden state and the infor...

Method used

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  • Automobile competitive product comparison method based on viewpoint mining analysis
  • Automobile competitive product comparison method based on viewpoint mining analysis
  • Automobile competitive product comparison method based on viewpoint mining analysis

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Embodiment Construction

[0034] The implementation steps of the technical solution are as follows:

[0035] Step 1. Data set acquisition

[0036] Step 1.1: Build a model dataset. The text preprocessing of the collected car user’s opinion and evaluation information first uses Python crawler technology to obtain the URLs of major car websites, and defines the car brand, user evaluation, and comment time as the extraction attributes for data acquisition.

[0037] Step 1.2: Data preprocessing, use Python regular expressions to filter the non-text part of the text evaluation information, and use the stammering word segmentation to process the text evaluation.

[0038] Step 1.3: Data labeling, mark the data processed in step 1.2 according to the descriptions of appearance, interior, space, comfort, fuel consumption, and handling, and use one hot coding method, which is represented as data set 1 as n is the total number of samples, and i is the subscript of one hot encoding. At the same time, mark the us...

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Abstract

The invention discloses an automobile competitive product comparison method based on viewpoint mining analysis. The method comprises the steps of firstly constructing an automobile user evaluation training data set, and then training a text topic extraction model and an LSTM-Attention training text emotion polarity discrimination model by using a deep learning network structure including a convolutional neural network TextCNN; in combination with two deep learning models of TextCNN and LSTM-Attention, obtaining an automobile user evaluation theme and theme emotion scores by using a pipeline processing mode, and finally outputting theme evaluation and emotion polarity by using the model to realize automobile competitive product comparison based on automobile user comment viewpoints. Compared with the prior art, automobile competitive product analysis comes from user comments, the method has the advantages of being high in authenticity and feasibility, and the model has good accuracy anduniversality.

Description

technical field [0001] The invention relates to the field of viewpoint mining and analysis of natural language processing, in particular to a method for comparing competing automobile products based on viewpoint mining and analysis. Background technique [0002] With the rapid development of the Internet 2.0 era, great changes have taken place in traditional lifestyles and business structures. The Internet accompanies every aspect of everyone's life. People are accustomed to leaving a large amount of text information on the Internet to express their opinions and emotions. With the government's vigorous support for new energy vehicles and the rise of smart connected vehicles, both indicate the diversified development and transformation of the automotive industry in the next few years, automakers need to know whether their products can meet the needs of consumers, but traditional research methods are due to Defects such as small sample size and low efficiency have been unable ...

Claims

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Application Information

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IPC IPC(8): G06Q30/06G06F16/35G06F16/951G06F17/27
CPCG06F16/35G06F16/951G06Q30/0629
Inventor 李天瑞乔东殷成凤王淑营贾真
Owner SOUTHWEST JIAOTONG UNIV
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