Academic Blog

I didn’t sleep well. I kept thinking about examples of using SQL in data mining algorithms. It’s getting one of my hobbies. If it’s your hobby too, please visit this thread. I know it’s nothing fancy, not even close to real-life data problems. However, if appropriately adjusted to practical applications, maybe it could lead to something useful? Anyway, half awaken and half dreaming about SQL, I attended the sessions.

The keynote today was a perfect example of the difference between dreams and reality. David Carlson spoke about one of those scientific megaprojects where nothing is easy, where everything needs to be resolved from scratch, starting with funding and finishing with science. With regards to the project’s goals, I especially liked the aspects of building predictive models. Yesterday we learnt about compound, unstructured and not in place data. Today we listened about data that doesn’t even exist yet. (I know that people usually talk about prediction models in a different style, but isn’t it tempting to describe it like this?) By the way, just to digress a bit, I remember a very nice paper about processing forecasting queries. Simple and bright idea… Nevertheless, for Dr Carlson and other International Polar Year participants simple and bright ideas are not enough. They need to adapt them to solve highly complex tasks, over highly complex data.

The next item in today’s schedule was the awards ceremony. The best ICDE 2009 paper is: “Histograms and Wavelets on Probabilistic Data” by Graham Cormode and Minos Garofalakis. It was presented in Uncertainties session. Well, I decided to attend Transactions session which was held in parallel. However, I’ll surely get back to this paper. It’s perhaps too early to talk about it, but there may be some analogies between processing uncertain data and the way we do rough computing on our Infobright’s Knowledge Grid. Please have a look at, e.g., February posts on our academic blog with this respect.

The best student paper is: “Double Index Nested-loop Reactive Join for Result Rate Optimization” by Mihaela Bornea, Vasilis Vassalos, Yannis Kotidis and Antonios Deligiannakis. I attended Query Optimization session where the paper was presented. (Although Data Mining 1 session was held in parallel. What a pity.) The speaker referred to several good papers on non-blocking join algorithms. It’s wonderful that further improvements are still possible. The session included also other interesting presentations about adaptive query processing and optimizations based on sampling and statistics. Again, I should probably refer to our Knowledge Grid. But that would be too much about Infobright in a single post…

Instead, let me go back to the awards ceremony. The most influential paper award goes to Kin-Pong Chan and Wai-Chee Fu, for the paper titled “Efficient time series matching by wavelets”. The original idea of conducting similarity search by transforming highly complex time series data into a space spanned over relatively small amount of wavelet-based dimensions has been extended in many ways. It was a great pleasure to listen to this presentation. Let me sincerely follow the speaker in her last sentence: I wish everyone of you a very good time series!

Best greetings,

Dominik