A Library Reader Classification Method Based on K-Nearest Neighbor Algorithm
When classifying reader types,there is a situation of cross classification for a certain reader to be classified,making it difficult to classify.On the basis of the sample data of 27 readers obtained by questionnaire survey,this paper proposes a method of using the K-nearest neighbor(KNN)algorithm to classify readers.The classification process of the algorithm is described in detail,and the result of an example is analyzed.Through the analysis,this method can effectively overcome the situation of cross classification,the classification process is easy to operate,and the classification results are scientific and reasonable,which can provide a reference for the library to improve the quality of service and reader satisfaction.
reader type classificationcross classificationKNN algorithmquestionnaire survey
万方数据
维普
