Collaborative Filtering Algorithm Based on Interior Design Furniture Recommendation Technology
In view of the difference between the traditional furniture recommendation results and the users'expectations,a collaborative filtering algorithm based furniture recommendation technology research is proposed.Aesthetic preferences,according to the interior of the original style,combining the user mining association rules between the elements,set a confidence threshold,narrowing the scope of processing,extraction of available information,submit testing after filtering,and repeat rule mining process,using collaborative filtering algorithm,to calculate similarity between users,analysis user trust relationship between weight and use the shortest path trust weights,recommend suitable furniture.Complete interior design furniture recommendation technology based on collaborative filtering algorithm research,design and simulation and control experiment,using the Pearson correlation coefficient con-trast,reflect the similar relationship between the user and the experimental results show that the collab-orative filtering algorithm is applied to the furniture is recommended,to Pearson correlation among us-ers value remains between 0.7-1.0,confirm the recommendation results compared with the tradition-al,more can meet customer expectations,to meet user needs.
万方数据
维普
