Research And Implementation Of Agricultural Information Recommendation System

In recent years,with the rapid development of Internet technology,many traditional industries relying on Internet technology have gradually moved towards the road of digitalization and intellectualization through digital transformation and upgrading.Under the social background of vigorous development of Internet technology,how to improve the informatization and intellectualization of agriculture has become a difficult problem in front of us.At present,many agricultural information platforms only realize the digitization of text information,but do not provide users with personalized and intelligent information services.Thus,this article designs an agricultural information recommendation system,and adds an improved collaborative filtering recommendation algorithm.By analyzing the behavioral data analysis and calculation of the target user,the user’s preference characteristics are tapped to synergistic filtration.Collaborative filtering recommendation in an invisible and interactive way provides users with personalized and intelligent agricultural information consulting services.The main research work of this paper is as follows:1.Analyze the development status of the domestic and foreign agricultural information recommendation system,tap the factors that restrict the development of the information platform of agricultural information platforms,and proposes and designs an agricultural information recommendation system based on distributed real-time computing by combining the Flink distributed stream computing engine.The system upgrades the traditional agricultural information platform from the optimization of recommendation algorithm and the construction of distributed recommendation system architecture.2.For the proportion of hot information in collaborative filtering recommendation algorithm is too large,which interferes with the user similarity metric calculation process,we propose an improved collaborative filtering algorithm based on the hot weight of information.And the improved algorithm model is verified and compared through the dataset.The effect after optimization is better than that before improvement.3.Based on the idea of distributed stream computing in the era of big data,we study and constructs the architecture of agricultural information recommendation system,and designs an agricultural information recommendation system based on distributed real-time computing.This system can effectively solve the problem of poor scalability of traditional systems,the upper limit of data storage is insufficient and it supports the computing performance of the dynamic telescopic system.4.Combined with the optimized synergistic filtering algorithm and distributed recommendation system architecture,the design and implementation of agricultural information recommendation system is completed.