Abstract
With the rapid development of e-commerce industry, online shopping has become a craze. With the rapid growth of transaction volume on e-commerce platforms, a large amount of transaction data has been accumulated. From the transaction information of these users, a lot of very valuable information can be mined, such as the defects of products and the actual needs of users. In view of the existing e-commerce transaction information collection method is not mature, in this paper, the electric business platform system architecture planning and design increases the function management module. In this paper, a new Naive Bayes model is established by using HBase distributed database instead of traditional database. Based on the optimization and extraction of the important transaction information in the product, the dataset of e-commerce transaction information is updated. Through the efficiency test of the collection method, the information scalability ability test, and the accuracy test, the important context was sorted out after integration, the sources of trading information were sorted out, and the data analysis of the collected information was conducted to optimize the information collection method and verify the feasibility of the method.
Highlights
With the further development of network technology into the era of Web2.0, e-commerce platforms are blossomed, social networks are getting bigger and bigger, shopping is becoming more and more convenient, and communication is becoming more and more convenient [1]. e amount of network data is growing exponentially
It can be difficult to sift through transaction information to determine shopping needs [3]. erefore, mining useful information from extremely large information sets through technical means has become a hot application of big data mining technology in e-commerce platforms, which makes this technology a new research hotspot
Wang et al [11] invented an e-commerce trading platform and e-commerce trading information collection method based on big data, which can overcome the shortcomings of existing technologies
Summary
With the further development of network technology into the era of Web2.0, e-commerce platforms are blossomed, social networks are getting bigger and bigger, shopping is becoming more and more convenient, and communication is becoming more and more convenient [1]. e amount of network data is growing exponentially. With the further development of network technology into the era of Web2.0, e-commerce platforms are blossomed, social networks are getting bigger and bigger, shopping is becoming more and more convenient, and communication is becoming more and more convenient [1]. The development of network technology has expanded the way to obtain information from the extremely large amount of data, the reality is that as the volume of data continues to accumulate, it is still very difficult and will become more difficult to obtain truly useful and comprehensive data [2]. Aiming at the user information of two websites, a web data extraction algorithm based on regular expression is designed. Wang et al [11] invented an e-commerce trading platform and e-commerce trading information collection method based on big data, which can overcome the shortcomings of existing technologies
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