Abstract:

Personalized recommender system has been widely used in electronic commerce, but there is very few recommender system designed for farmers. According to the actual situation and the existing conditions, a farmer personalized recommender system based on latent semantic analysis is researched and designed. Latent semantic analysis can overcome the polyseme and synonym problems and easy to calculate, which improves the efficiency of the recommender system. These methods and treating processes have certain reference meanings to other recommender system.

Key words: farmer, latent semantic analysis, personalized recommender system