Research on User Access Pattern Mining Based on Web Log

Abstract

Aiming at the field of e-commerce, this paper analyzes e-commerce user behavior based on the data characteristics of e-commerce back-end logs and constructs a user behavior mining model. On the basis of Web user behavior theory, it analyzes user behavior based on interactive content. Based on the background of big data, the traditional data mining algorithm is further optimized, which greatly improves the operating efficiency of the algorithm. At the same time, a distributed file storage structure is adopted to improve the fault tolerance of system data processing. This paper studies the advantages and disadvantages of collaborative filtering recommendation algorithms. The Web user behavior mining system constructed in this paper can conduct multi-dimensional and efficient mining. It helps e-commerce merchants and content providers to understand their users and achieve better commercial value through precise marketing and accurate recommendations, and complete the upgrade of data-driven services.

High-Concurrency Big Data Precision Marketing and Advertising Recommendation under 5G Wireless Communication Network Environment

“…K-means algorithm is used in the process of cluster analysis. Each sample data point is divided into different groups by repeated iteration, and the distance between the sample data point and the centroid of the group is compared, so that the distance between each sample point in the same group and the distance between the sample data point in different groups are the smallest [15]. In the K -means clustering algorithm, Euclidean distance is generally adopted to measure the distance between data sample points.…”

E-Commerce Data Mining Analysis based on User Preferences and Assiciation Rules

“…Recommended Data Interaction Interface Modules. This module aims to realize the adaptation of commodity recommendation and trading interface [19]. The data collection problem of the mall record center involves data type, data date, data channel and so on.…”