Dynamically Updating the Knowledge Regular Library for BBS Public Opinion Analysis System with Apriori Algorithm

An important element of BBS public opinion analysis system is to update the contents of knowledge regular library dynamically adding sensitive words constantly to knowledge regular library. Apriori algorithm is classical algorithm of mining association rules. This paper presents a new method of adding the contents of knowledge regular automatically using association rule models. Experimental results show that the system obviously improves the accuracy of monitoring BBS public opinion by means of this algorithm.