Abstract: The road traffic safety is a public safety issue.The number of deaths due to traffic accidents account for the highest proportion in all accidents every year.With the development of big data intelligent analysis technology,the traffic accident data are extesively used to trace the causes,it is helpful to propose specific measures to avoid and prevent the occurrence of traffic accidents.According to the characteristics of diversity causes of traffic accidents,this paper proposd to use the news’ data of traffic accident combining with a wide range of news’ authenticity and characteristics timeliness to do the analysis of factors and the liability of traffic accidents.Taking the traffic accident news in Sina as the data source,the relevant factors of traffic accidents are extracted from it.In terms of the limitation in classic Apriori that only applies to a single dimension association mining and needs to scan database frequently,an improved multi-va-lued attribute Apriori algorithm was proposed.Focuing on the traffic accident data of provinces and cities,a variety of combination factors which lead to these traffic accidents were mined,thus the rules of frequent traffic accidents in pro-vinces and cities were summarized as the basis for taking preventive and regulatory measures.

Key words: Data mining, Database, Multi-valued attribute association rules, Traffic accident