I'm a CS master student focusing on data mining. Now I'm doing my master thesis and the contribution of my thesis is to compare different approaches/methods of one topic (e.g. clustering of text documents). What I did so far is looking at the state of the art on the topic and read the papers. However now I need to think of what to compare. Of course there is the obvious comparison question: which method give best results? But that is so obvious. My supervisor once mentioned to see how those methods compare their results and look that maybe there is a better way to compare the results of the methods. That was helpful to me to think about questions like this. But still I'm so stuck and I can only think of obvious stuff. This is the first time I do something like that.
I'm sure some of you went through something like this, so I was wondering if you can even tell me some /basis/ stuff and questions that people address when they compare methods in computer science. My main questions to you are:
1- When I read the papers of the methods to compare, in which way I should read it? Critical? Questionable? What to look exactly in them?
2- Is there a general scheme for comparing methods in academia?
3- As for a master thesis, what which stuff are a must-do for comparisions?
4- Any great references/papers related to comparisions that could help me?