Design And Implementation Of Search And Recommendation Engine For E-commerce Website

With the development of the Internet and e-commerce,e-commerce websites provide users with more and more choices,But it also makes it difficult for users to find their favorite products quickly in a large number of products.How to let users quickly find the products they needed,how to discover the potential needs of the users,is very important for e-commerce websites.Therefore,search and recommendation engines have very broad development and prospects in e-commerce systems.However,with the continuous expansion of e-commerce websites,ecommerce websites are also facing a series of challenges.In view of the main challenges faced by e-commerce websites,this paper mainly explores and studies the key technologies such as search and recommendation algorithm design and system architecture in e-commerce websites.This paper analyzes and studies the problems and challenges in cur rent product matching and the corresponding solutions.It also introduces the design of search and recommendation engines in detail and implements a high concurrent distributed search and recommendation engine.The search engine mainly includes four major modules: query word prediction,indexing,sorting and model.The indexing part includes incremental index,real-time index and full-quantity index.The sorting module includes three parts:accurate sort,rough sort and rearrangement.The matching aspect considers the historical data of buyers and sellers,query condition information and commodity information.Based on these data,the logistic regression model is trained to improve the matching accuracy.In the aspect of recommendation,Through collaborative filtering recommendation algorithm and content-based matching algorithm analysis and effect comparison.The content based recommendation algorithm is found to have a higher conversion rate than the collaborative filtering algorithm,and the content-based recommendation algorithm increases the recommended conversion rate by increasing the category weights.The system functional structure design,detailed design,database design and class diagram relationship design are realized.After system testing,the search and recommendation engine scheme designed in this paper has achieved good results in the accuracy of search and recommendation,satisfying the user's functional requirements and performance requirements.