I have list of log comments in CSV file. I want to cluster those log comments using K-Means and after that I want convert each cluster comments into general form. for eg. I have bunch of comments in one cluster which starts from "Reservation number failed......" and I want to convert those comments into particular comment like "Reservation failure".
I can achieve this by giving specific name to each cluster after seeing each cluster. But I don't want like this. I want to create intelligent model which automatically create generalized comments for me.
I would not like to assign name to each cluster. Basically I am done with clustering part. that is, I have lets say 3 clusters as below
- cluster 0 : list of comments like "Reservation number failed......", total comments: 15
- cluster 1 : list of comments like "Request timeout failed due to ......", total comments:9
- cluster 2 : list of comments like "Dinning reservation successfully completed...", total comments: 5
I want to build model that intelligently assign name to each cluster by its contents. for eg .
- cluster 0 will get name as "Reservation failure"
- cluster 1 will get name as "Request timeout failure"
- cluster 2 will get name as "Dinning reservation successful"
if after training more data with some different comments. it should create another cluster and assign the name as per content.