ok, that could be an assumption of course. I more or less expected that. Anybody who uses mnemosyne regularly, adds all words he is using, has just some some small random influence on particular items by other methods is the "regular". and everybody else creates noise...
Just thought it's pretty hard to assess the noise level - as checking on myself I found that me alone am creating 3 types of "noise". But then again, probably it is possible to identify what kind of noise gets generated by the particular "misuse" pattern and try to asses the level/filter it off. And datasets with big interruptions can be included or excluded to see how they modify the picture. Good luck, and I hope this data plan brings some interesting results. In fact I think that info about item being a duplicate to other items could be included in the upload as well. Of course there are still ways to introduce them without getting "caught".. I keep different courses in different databases, so duplicates would never show up as such :-/ On Feb 7, 9:45 am, Peter Bienstman <[email protected]> wrote: > On Sunday, February 06, 2011 04:41:44 pm normunds wrote: > > > I wonder is there a consistent interpretation of mnemosyne gathered > > data possible. Has anybody analysed it > > Not really, Mnemosyne 2.0 is my priority now. > > > and what assumptions do you > > make and how do you filter of "wrong data" from "regular ones". Or if > > not, how do you try to account for presence of some unexpected use > > patters. > > It's an enormous dataset, with many thousands of users. The assumption is that > any 'particularities' will be just noise and overshadowed by 'regular' > entries. > > Cheers, > > Peter -- You received this message because you are subscribed to the Google Groups "mnemosyne-proj-users" group. To post to this group, send email to [email protected]. To unsubscribe from this group, send email to [email protected]. For more options, visit this group at http://groups.google.com/group/mnemosyne-proj-users?hl=en.
