iNNOVATION Insights, Global的动态

Transcript

We're clean the data by remove their noise such like the special character number, the stop word and some handle misspelling. This kind of noise is no meaningful, so we will delete remove all of this. So after we got the cleaned data, so we select the model to do the. Centimeters. Annual analysis. And then we got the results showing the the comma is positive, negative or neutral. Something like a we will filter the world. If the comments have the good or wonderful on this kind of the world, which means this is a positive. On the other hand, if the comma have the bad and some the bad word is this is negative and if they. And and also have the neutral comma.