Data Mining Technology Based on Association Rules Algorithm

Abstract

The current data mining technology has the mismatch problem of mining keywords and used words, which leads to low mining precision and low efficiency. In this paper, a new data mining algorithm based on association rule algorithm is proposed. Firstly, the weight of the keywords in the data mining process is calculated by using the TF-IDF function. Based on the analysis of the association rules algorithm and the vector space model, the information retrieval model is constructed. On the basis of this, the association rule algorithm including the initial mining items is used to establish the rule database, and several words with the highest degree of relevance to the mining words are selected as the extension words, which is combined with the initial mining into a new mining. Finally, the clustering analysis of new mining results are carried out by K-means clustering algorithm, and according to the descending order, the relevance is ordered, to output mining results. The experimental results show that the algorithm is accurate and efficient.