Lately one of my favorite things to do at night is to just pick up a subject and brainstorm about it, writing down whatever I feel like is relevant. It’s quite interesting, because after I finish the activity I read back what I’ve written and enjoy how naive and contradictory all my ideas are.
Let me give you a hypothetical example. Let’s say that today’s subject is knowledge acquisition. So I start by writing:
– Knowledge is defined by the relationship between elements
– There are no elements, just the relationships
– The absolute is defined by a relative sense to what is culturally or personally defined as the absolute point
And there is goes… It’s a fusion of not very actionable pieces of ideas. Not very exciting then, but it continues, and gets worse:
– Branch traversal is interrupted when relationships are not found or when they become too low in interest to continue
– Interest is defined by the types of relationships between things
– Types are also relationships to moods or goals
Conclusion, I’m back to saying that there have to be some absolute elements to knowledge: here the “moods and goals”. How can you think of knowledge without being able to point to something and say: the book… the table… the book is on the table (sorry for you native English speakers).
Anyway, it’s fun. And what makes it more interesting is that I don’t expect to get anything out of it. I’m through with creating a new project every other day like a couple of weeks ago. Time to relax and just keep my mind active.
Talking about keeping my mind active, I was reading a paper earlier today: “Mining Nonabiguous Temporal Patterns for Interval-Based Events” by Shin-Yi Wu and Yen-Liang Chen. It’s an interesting paper where the authors propose methods to find patterns on the relations between interval-based events by classifying pair-wise relations using a very simple set of 7 possible relations. It’s pretty and all, but when you get to real world case, the stock analysis, they make a whole set of simplifying transformations that make the problem, let’s say, silly. They use three “event types”: (1) the stock price increases for at least 3 days, (2) the stock price decreases for at least 3 days and (3) the stock price increases and decreases at least 3 times. Also they discuss 3 period lengths: week, month and season. Talk about arbitrary definitions here. All stock prices go up and down at least 3 times in a week. They usually do that in a 5 minute period.
In any way, there are some interesting ideas in the paper, like the process to try and predict stock movement with their correlation patterns that was found. Interestingly some of their graphs show an almost random predictive accuracy for the interesting things and very good accuracy for behaviors like “season trends”. Not very meaningful, I guess. Also what I liked about the paper that sparked the brainstorming that I’ve mentioned before is that what they mine is not the events themselves, but the relationship between the events.