Application of frequency similarity algorithm in audit rulebase
Lixia Qiu · Computer Engineering and Applications Journal · 2012
As sentence semantic similarity algorithms based on HowNet ignore the weight that different words have different contribution to the sentence similarity value,the similarity result is not reasonable based on these algorithms.In order to solve this problem,the paper improves the traditional semantic similarity algorithm by adding a frequent function of words in corpus as a weight factor into the final sentence semantic similarity algorithm,this function can decrease the proportion that high frequence words devote to high sentence similarity value and improve the accuracy.In aspect of algorithm application,it is known that audit methods summarized by auditing administration are always reduplicated and not clear,in order to reuse these audit methods,this paper builds an audit rule base according to the audit methods.On this basis,it adopts the improved semantic similarity algorithm to calculate the similarity value between user input and rules in audit rule base.It will return the corresponding audit methods of the audit rules whose similarity value satisfy the given threshold,auditors can pick the most appropriate audit method to audit the programme.The application shows the algorithm improves the audit efficiency.