Bug reports can be a great source of information, but usually finding the information requires extensive work in reading through all of the discussions and understanding the details about it.
Could it be that machine learning can be used to extract meaningful information out of that? That's what this project is about. The idea is to explore some different methods and see what the results are.
Here are some rough ideas on what to try:
- sentiment analysis
As a dataset, the plan is to collect SLE bugs and openSUSE bugs from our very own bugzilla and use this data to train/validate some models.
Looking for hackers with the skills:
Nothing? Add some keywords!
This project is part of:
Hack Week 20
This project is one of its kind!