Recommendation System of Crop Planting Books Based on Big Data
The development of agriculture plays a very important role in the economic development of our country. With the continuous development of China’s national economy, how to achieve the recommendation of suitable crop cultivation or formulate a reasonable crop cultivation program, and then improve food production, has become a research hotspot in the field of agriculture. At present, the practical application value of agricultural information platform in our country is not great, and the research on crop planting recommendation system is very few. In order to effectively implement the crop planting book recommendation system, this paper summarizes several common recommendation algorithms and proposes an improved collaborative filtering recommendation algorithm. Experiments show that the improved recommendation algorithm proposed in this paper has certain advantages. With the arrival of the era of big data and the further research on recommendation system, this paper proposes a crop planting book recommendation system based on Hadoop for large-scale data processing. By carrying out two groups of experiments with different number of users and number of projects, this paper proves that the method is effective in processing large-scale data. The results show that the research of crop planting book recommendation system based on big data plays an important role in helping farmers get relevant planting information as soon as possible, and has reference value for information construction in agricultural field.