The Association Rules Aided Genetic Algorithm for Text Classification

Information overload is a serious issue in the modem society. As a powerful method to help people out of being ”lost” in too much useless information, Information Retrieval is getting more and more important. Automatic text classification is one of the most important tools in Information Retrieval. This article proposes a new text classification method called Association Rules Aided Genetic Computing Method (ARGCM). The main contribution includes: 1) The Association Rules Aided Genetic Algorithm (ARGA) for text classification, 2) Different from existing work, the fitness function are coded under the assistance of the association rules mined by Apriori_ARGACM algorithm, 3) Implementing the genetic procedures: AGACM_Roulette_Selection, AGACM_Xover and AGACM_binaryMutation and giving extended experiments. 4) The experimental results show that the ARG algorithm is superior to other common methods. A B-Vector with a score 3513.6 can be achieved after running ARG algorithm after 50 generations.