Abstract: In order to effectively utilize the large number of hidden danger records in production process accumulated in the management of HSE, realize the early-warning of hidden danger and solve the problems such as low efficiency, high subjectivity of manual data analysis, a TF-IDF visual model for early-warning of hidden danger was established. Firstly, the Apriori technology was applied to mine the potential associations between various hidden dangers. Then TF-IDF algorithm was introduced to optimize and sort the association rules to find out the critical associations among hidden dangers. Finally, visualization technology was used to display the mining results intuitively. Results show that the proposed TF-IDF visual model can realize the early-warning of hidden danger quickly and accurately, that the optimization of association rules solves the problem of strong dependence of Support in Apriori algorithm, and that mining results can provide the direction and give support for enterprise safety management.

Key words: term frequency- inverse document frequency(TF-IDF), Apriori association analysis, optimization of sorting, early-warning of hidden danger, text visualization