Here are some impressions of the ACM Data Mining Camp , held on Mar 20, 2010 in San Francisco.
Mining Data Mining Camp Impressions
Data Mining Camp ... uses an Open Space Technology (OST) approach - no formal agenda beyond the overall data mining theme. Except the expert panel, sessions are compiled on-the-fly, based on real-time interest and participation.Overal, the unconference - with a new location and almost doubled attendance - was a success - even if judging only by results of twitter sentiment analysis tools (subject of a not-so-successful data mining camp topic) - tweetfeel, twitrratr and twendz.
Obviously, completely ad-hoc sessions could be a bit chaotic - even though organizers briefly presented their topics and rooms were assigned adter counting a show of hands, there were surprises and unmet expectations.
Many people preferred traditional formats to round table discussions - tutorials were the most attended sessions, while discussions were either the most or least liked sessions. The arrangement of chairs and the look of the room preset expectations of participants - some organizers did not really plan to present but had to come out with slides or tutorials. Great observation by Dominique Levin:
NextGenCMO Room shape impacts success of un-conference: Circle of chairs works wonders to solicit audience participation at #dmcamp. Circle time!
Another interesting observation was that Linkedin turned to be the most efficient marketing tool for the conference. Twitter and other social networks did not seem to have an impact. The explanation could be very simple though - age group and education level of the target audience.
The venue was much more hospitable to barcamp type of event than Hacker's Dojo last time. The participants are a weird mix - there are a few real experts, lots of practioners, and lots of newbies trying to get a hold of the field. Inflow of people interested in data mining has to have something to do with the fact that companies are really after people with these skills. At the opening session there were NetFlix, eBay, Yelp, Digg and lots of startups pitching their open job positions. If you are a Hadoop/data mining jockey it looks like you can land a job in SV in a matter of seconds.Initial expert panel was highly acclaimed. The guys were really direct, honest and interesting. A few quotes:
* Joseph B. Rickert: "Size of your data and time you have to analyze it are reversely proportional"
* @hughewilliams: "Data miner vs Statistician skills - ability to write code"
* Ted Dunning's preconditions for data mining: 1) data exists 2) someone benefits in a concrete way
My Experience at ACM Data Mining Camp
... Status of MahoutThis one was particularly exciting. Dr. Ted Dunning, a committer for the Mahout project stated that the purpose of Mahout (muh-hoot) is to make machine learning and data mining algorithms scalable. The purpose is not to make the most efficient or highest performing algorithm. In particular, Mahout is built on top of Hadoop so algorithms can take advantage of map-reduce. Mahout is not currently a top-level project, but a subproject of Lucene. It may become a top-level project, like Hadoop, some time in the future.
Mar. 20, 2010 ACM Data Mining Camp
On March 20, 2010 in San Jose at the eBay Town Hall, ACM held a Data Mining Camp. It was more fun than SXSW. I want to thank the people of eBay for accommodating such a large crowd and the ACM volunteers who kept it all running. Tricia Hoffman of ACM moderated panelists Mike Bowles od Bowles Consulting, Ted Dunning of DeepDyve, Greg Makowski of Golden Data Mining, Joseph Rickert of Revolution Computing, Giovanni Seni of Santa Clara University, Michael Walker of Stanford University and Hugh Williams of eBay.