Design And Implementation Of New Agricultural Technology Recommendation System Based On Semantic Analysis

At present,China is experiencing a new stage of agricultural transformation.In the process that marches toward an agricultural strong country,Informationization plays an important role in improving agricultural quality,benefit and competitiveness.The application of agricultural informatization in the field of agriculture is still very low.When people need new agricultural technology,they can only query through the network search engine,which is slow and inefficient.To a certain extent,this has hindered the transformation efficiency of agricultural scientific and technological achievements and affected the application and development of agricultural information technology.Based on this,this paper designs and develops a personalized recommendation system for agricultural new technology.In the process of system design,this paper mainly improves the traditional collaborative filtering algorithm,which is embodied in the fusion of BIRCH algorithm and K-means algorithm for cluster analysis.In addition,according to the current situation that the collaborative filtering algorithm relies on the specific score of the project,HowNet builds a semantic comment dictionary,and through the sentiment analysis of the user’s comment statement,the emotional tendency value of the comment word is obtained,thereby expanding the project score data.After that,by using the relevant data sources,the recommended algorithm model that is more suitable for the agricultural field is analyzed and obtained.Finally,a new agricultural technology recommendation system is constructed by using zhis model.The overall structure of the system is reasonable and the language design is natural,which meets the personalized information needs of users and successfully realizes the recommendation of information.