Real Estate Marketing Adaptive Decision-Making Algorithm Based on Big Data Analysis

Abstract

Aiming at the problems of low stability and efficiency of marketing decision-making and large complexity of marketing decision-making in the current marketing adaptive decision-making algorithm, a real estate marketing adaptive decision-making algorithm based on Big Data analysis is proposed. By analyzing the concept of Big Data, using the Big Data distributed computing architecture, researching the data mining-related algorithms. By constructing an association rule algorithm, mining the rules between real estate marketing and related factors. Based on the Spark-distributed computing platform, an optimization idea of association mining is designed. Decision tree algorithm is used to select discrete and continuous attribute features. According to the characteristics of real estate marketing data and the weight-based discrimination method, the decision tree pruning algorithm is optimized using the classification accuracy, stability, and complexity criteria, and the adaptive decision-making model of real estate marketing is constructed to realize the adaptive decision-making of real estate marketing. The experimental results show that the proposed algorithm has high stability and efficiency in real estate marketing adaptive decision-making and can effectively reduce the complexity of marketing decision-making.