基于信息熵的规则分类算法在农业信息推荐中的应用研究

The research of classification rule based on information entropy algorithm on agricultural information recommendation

农业信息迅速、即时地更新给使用者带了极大的便利,但与此同时,由于大量农业信息的快速产生,使得人们从中难以即时地获取有效的信息。在对依据农户地域特征进行农业信息推荐的研究中,提出1种基于信息熵的规则分类算法,此算法能够以很小的代价对农业信息中包含的地域信息进行划分,从而可以较好地匹配农户的地域特征。经试验测试,在农业信息推荐中应用基于信息熵的规则分类算法明显提高了信息推荐的准确率。

The rapid and real-time updata of agricultural information has brought convenience to people.Meanwhile,because of its speed being far beyond the using efficiency of people,it makes people difficult to acquire effective information.In the research of real-time information recommendation according to farmers interested topic information,a learning algorithm based on the rule classification was put forward,which supported incremental mechanism.It corrected the deviations from the topic information with little cost,and it expanded the content of the topic covered.The rule classification based on information entropy has improved the accuracy of agricultural information recommendation in the laboratory test.