What would it take to convince you:
- ... to buy a spam filter?
- ... to win a nobel prize for spam filtering?
- ... to publish a paper?
- ... to grant a PhD?
Here are a few of the many ideas that surfaced:
- develop a system that generates undetectable spam
- create a high-accuracy system that performs automatic unsupervised learning so that the user is never bothered with spam again.
- prove the problem of spam is the same as a currently known solvable or unsolvable problem
Myth - a widely held, but false belief or idea (in this context). Myths get us into trouble when we say they are false, but we act like they are true.
- Computer Science isn't science, it's just processing.
- The right questions and their possible answers are obvious.
- To find good research problems just look at what everyone else is doing.
"I skate to where the puck is going to be, not to where it has been.” - Wayne Gretzky
- Science is just common sense.
Myth: Good research is based on what your undergraduate degree trained you to do well.
- All findings in major journals are true.
- Failure is bad.
Design an experiment to learn regardless of the outcome.
- Great researchers are born, not made.
- To be successful I just need to show my system is better.
- To be successful I have to work all the time.
Focus on productivity.
- To be successful, I just need to do more of what I'm already doing
1) think harder or 2) code more
- Applied Math/CS is not as good as theory
"The code you write today won't run in five years. Get over it. What will be used? It is the understanding derived from running the code."They also referenced two great books: The Structure of Scientific Revolutions and Sciences of the Artificial.
See the website for last year's version.
If you want to learn more about methods to conduct constructive Computer Science research, I recommend David Jensen's Research Methods Class. The notes from the Spring 2008 are available.
Upon reflection, what struck me is that sometimes I have a tendency to follow what's hot right now rather than looking ahead to the future. Don't follow into this trap.