Mining Associated Factors about Emotional Disease Bases on FP-Tree Growing Algorithm

The objective of this paper is to mine the useful information from anger and anger-in life events questionnaire, Eysenck Personality Questionnaire (EPQ) , State Trait Anger eXpression Inquiry (STAXI) Scale, Trait Coping Style Questionnair (TCSQ), Perceived Social Support Scale (PSSS) , anger and anger-in predisposition questionnaire, anger and anger-in Physiological State Questionnaire (PSQ) and a number of test indicator data, Look for associated factors, fumble rule, guide people to do early prevention and treatment. In this paper the forming process of FP-tree of the Emotional database is analyzed, the algorithm of structuring frequent model FP-tree and mining frequent itemsets are designed, the database information scanned is recorded by using FP-Tree growing algorithm through state-trees, frequent itemsets meet minimum support required are generated through reducing the search space of project sets and scanning database only one. The mine of all factors associated with emotional disease is actualized. The experiment shows strong factors associated with emotional disease can be mined from database system by the mining algorithm bases on FP-Tree frequent itemsets. The mining results can provide scientific basis for the analysis, prevention and treatment of symptoms.