Classification and Mining Algorithm of E-commerce Big Data Based on User Behavior Data

Classification and Mining Algorithm of E-commerce Big Data Based on User Behavior Data

연구 분야: Databases

학회: 2023 International Conference on Telecommunications, Electronics and Informatics (ICTEI)

Internet data is growing exponentially. All kinds of complicated texts, pictures, videos and even emoticons make people dazzled and cannot distinguish key information. For young people, online shopping has become the most common form of shopping. And it also plays a considerable role in economic and social development, and has become a force that cannot be ignored. It covers the entire process of user purchase, from traffic introduction, search, product browsing, add-on purchases, payment and other operations. Using dimensional parameters as important parameters of data mining for algorithm modeling, it can realize efficient data mining in complex networks. However, when the similarity of the data content is high, the data mining efficiency and accuracy are obviously reduced. Favors e-commerce platforms to obtain accurate user portraits, so as to improve consumer guidance or commodity push information. As a result, shopping is no longer limited by time and space, and more people are willing to accept this kind of online shopping behavior. Predict the sales of goods through data mining, and adjust their business models and related business systems. First, the user data is modeled, and then data mining is carried out to enhance and stabilize the anti-interference in the mining process, but its actual application field is more limited. In this paper, based on the current mode of e-commerce big data application, from the perspective of user behavior data, the ecommerce big data classification and mining algorithms are analyzed.