Constructing Tourism Association Words Set Based on Association Rule Mining

It is difficult for traditional data mining algorithms to mine semantic information from text set because of its complexity and high dimension. To solve this problem, the semantic categories of words appearing in tourism emergency reports are studied, and a semantic association rule mining algorithm is presented based on these categories. Association words are also gained from these rules, which can better describe the semantic contents of the texts. Quantum-inspired genetic algorithm is utilized to improve the effectiveness of rule-searching process. Experiments show the better results than traditional methods.