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Abstract
The recommendation engine is similar to the function of the product recommender in our real life, which provides great convenience for people to choose the appropriate decoration scheme in the process of interior design and decoration. A home improvement website or company can design a suitable recommendation algorithm to provide home improvement program recommendation services for users with decoration needs. After understanding the user behavior of the home decoration website, this paper proposes an interior design scheme recommendation method based on an improved collaborative filtering algorithm. The method designs a collaborative filtering algorithm that combines multilayer hybrid similarity and trust mechanisms. Fuzzy set membership function is introduced to correct users’ rating similarity, and users’ interest vector is extracted to calculate users’ preference for different types of items. The algorithm dynamically fuses those two aspects to obtain the mixed similarity of users; meanwhile, the user’s hybrid similarity and trust are fused in an adaptive model. Then, the user neighbor data set generated based on the overall similarity of users is used as a training set, taking the item scores and features into consideration. On the one hand, the users and the projects are taken into account as well. The final prediction score is more accurate, and the recommendation effect is better. The experimental results show that this method can recommend interior design schemes with high performance, and its performance is better than other methods.
Highlights
With the sustained and rapid growth of China’s national economy and the increasing per capita income, coupled with the strong promotion of China’s real estate industry, the demand of our interior design and decoration industry has remained strong
Some interior design item data sets are used as test objects to test the performance of collaborative filtering technology in the interior design project recommendation method proposed in this paper
Due to the shortcomings of current interior design recommendation methods such as large errors and long time consumption, an interior design project recommendation method based on an improved collaborative filtering algorithm was designed to obtain ideal interior design project recommendation results
Summary
With the sustained and rapid growth of China’s national economy and the increasing per capita income, coupled with the strong promotion of China’s real estate industry, the demand of our interior design and decoration industry has remained strong. The rapid development of the Internet has promoted people’s participation and demand on the Internet. The number of Internet users has increased to a considerable degree. Online shopping has penetrated into every aspect of our daily life. Taobao, Jingdong and many other websites are relatively successful and mature e-commerce platforms, while home decoration e-commerce has not yet become mature. As the online shopping experience of home decoration is not high, users’ purchasing desire is not strong. While the consumption of home decoration is increasingly hot in recent years, it is relatively backward in ecommerce [1]
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