Intelligent classification method of Web database search results based on a weighted random forest
The search results of Web database have the phenomenon of complex data and a large number of data.The complex relationships between data are in a fuzzy state,resulting in a small difference in membership,and the classification process re-quires many iterations and low efficiency.Therefore,the intelligent classification method of Web database retrieval results based on the weighted random forest is proposed.Data features of the Web database search results were extracted and the Web database search results were processed redundantly.After redundancy processing,the weighted random forest technique was used to deter-mine the range of fuzzy membership of Web database search results.Finally,by calculating the classification weights of samples,a Web database search result classifier is designed to realize the intelligent classification of Web database search results.The experi-mental results show that the F1 value of this method is above 95%,and the longest classification time is only 7.8 s,indicating that the method can complete the classification task more quickly and accurately.
weighted random forestWeb databasefuzzy membershipintelligent classification method
万方数据
维普
