Automatic Essay Scoring Model Based on Multi-channel CNN and LSTM

2021 ◽  
pp. 337-346
Author(s):  
Zhiyun Chen ◽  
Yinuo Quan ◽  
Dongming Qian
Keyword(s):  
Scoring Model ◽  
Model Based ◽  
Essay Scoring

scholarly journals Exploring the Feasibility of an Automated Essay Scoring Model Based on LSTM

2021 ◽  
Vol 24 (4) ◽  
pp. 223-238
Author(s):  
Kangyun Park ◽  
Yongsang Lee ◽  
Dongkwang Shin
Keyword(s):  
Automated Essay Scoring ◽  
Scoring Model ◽  
Model Based ◽  
Essay Scoring

Marketing customer response scoring model based on machine learning data analysis

2020 ◽  
pp. 1-11
Author(s):  
Tang Yan ◽  
Li Pengfei
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
Data Extraction ◽  
Machine Learning Algorithms ◽  
Customer Relationship ◽  
Customer Data ◽  
Modeling And Analysis ◽  
Scoring Model ◽  
Model Based ◽  
Learning Data

In marketing, problems such as the increase in customer data, the increase in the difficulty of data extraction and access, the lack of reliability and accuracy of data analysis, the slow efficiency of data processing, and the inability to effectively transform massive amounts of data into valuable information have become increasingly prominent. In order to study the effect of customer response, based on machine learning algorithms, this paper constructs a marketing customer response scoring model based on machine learning data analysis. In the context of supplier customer relationship management, this article analyzes the supplier’s precision marketing status and existing problems and uses its own development and management characteristics to improve marketing strategies. Moreover, this article uses a combination of database and statistical modeling and analysis to try to establish a customer response scoring model suitable for supplier precision marketing. In addition, this article conducts research and analysis with examples. From the research results, it can be seen that the performance of the model constructed in this article is good.

Sign in / Sign up

Export Citation Format

Share Document