Research Of Decision Support System Design For Choice Difficult In Clothing Online Shopping

The choice of overload is an inevitable phenomenon of world economic development since the industrial revolution.Especially in today's rapid development of artificial intelligence,the choice of overload is becoming more and more serious.Product selection overload seriously affects the efficiency of consumer decision-making,increases the cost of thinking about consumption,and contradicts today's pursuit of efficiency.Today's research on the impact of selection difficulties is mostly theoretical research,lacking effective decision aids.Taking the clothing online shopping scenario of e-commerce consumption as an example,this paper conducts an experimental study on the selection of difficult behaviors under the clothing online shopping scenario,and judges the selection of difficult behaviors through the decision-making behavior of consumers,and studies the difficulty identification mechanism.Based on the difficulty of selection,combined with the expert system in machine learning,the decision-making assistance method for clothing online shopping was developed,and the decision aid system was developed.The feasibility of the method was verified by decision cases.The main research contents of this paper are as follows:Firstly,the research on the difficult behavior of the selection of clothing online shopping activities was carried out.Based on the selection of experimental paradigms and tasks of difficult behavior representation,the video of decision-making behaviors and decision-making preferences of 41 subjects were collected,and the performance indicators of difficult selection were obtained as follow-up development decisions.The selection difficulty in the auxiliary system identifies the mechanism rules.Secondly,the relationship between various indicators and decision-making difficulties in decision-making behavior is studied.The correlation analysis between the selection of difficult behavior indicators and the Pearson correlation is proved by using the analysis of variance,rank sum test and Pearson correlation.Then,based on the expert system,the design of the clothing recommendation module in the decision support system is mainly focused on the recommendation of the clothing style.Using the production rule form to build a knowledge base containing information on collocation knowledge and clothing goods and user physical features,occasions and weather information,and designing the inference engine by adding an index table in the blackboard structure,simulating the clothing thinking expert thinking process,generating Daily matching list.Finally,the prototype of the clothing online shopping selection difficulty decisionmaking system was developed,and the daily matching and online shopping decisionmaking auxiliary functions were realized.The feasibility of the system was verified by decision cases and matching recommendation evaluation.