Analyzing the interestingness of association rules extracted from vaccine medical report

摘要

Vaccines have been one of the effective public health medications. Although, vaccines are provided to protect from life threatening diseases but these pharmaceutical products can cause adverse effects. This paper presents a method that adopts a text mining system to discover association rules which are interesting and extracted from vaccine medical reports. Text mining technique has been used to extract interesting patterns or knowledge from large text corpus. In this paper medical reports of those patients who suffered from adverse effects of vaccines have been used. The symptoms of patients in medical reports are categorized into background knowledge and target documents. Further the evaluation of interestingness of extracted association rule is analyzed by computing the semantic distance between predecessor and successor of association rule.