If the user follows some pattern in his check-ins and deviates form this pattern I want NuPIC to indicate anomalous behaviour. So in case a user is trying to fake his location it may be verified in some manner.
On Tue, Mar 10, 2015 at 10:55 PM, Matthew Taylor <[email protected]> wrote: > It is possible, but what are you trying to get out of the analysis? > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > > On Tue, Mar 10, 2015 at 10:23 AM, Manal Bhingardeve > <[email protected]> wrote: > > Will NuPIC produce some results for those users with >500 check-ins? > which > > is about 25 per month. > > > > On Tue, Mar 10, 2015 at 9:53 PM, Matthew Taylor <[email protected]> > wrote: > >> > >> Ok, so I'm assuming a bit here, but... > >> > >> 107092 users with 6442892 total checkins over the course of (about) 20 > >> months.... then the average checkings per user per years is > >> (6442892/107092) / 20 = 3 checkins per month. > >> > >> If you want to analyze users individually with only 3 checkings per > >> month, that is not a very fast stream of data. I'm not sure you're > >> going to get anything out of it with NuPIC. > >> > >> However, if you wanted to try to analyze population trends in the > >> complete data set over time, it might be worthwhile to try with over > >> 300K total checkins per month, but you wouldn't be able to get any > >> analysis out of it for individual users. > >> > >> Perhaps you could group the users by geographic location to increase > >> the number of data points in a model if you aren't interested in > >> complete population analysis? > >> > >> --------- > >> Matt Taylor > >> OS Community Flag-Bearer > >> Numenta > >> > >> > >> On Tue, Mar 10, 2015 at 7:26 AM, Manal Bhingardeve > >> <[email protected]> wrote: > >> > Hi Matt, > >> > > >> > I would like to get indications of anomalous behaviour. > >> > The patterns should be isolated to each person. > >> > The data consists of check-ins of users over the period of Feb. 2009 - > >> > Oct. > >> > 2010 > >> > These are some details about the data. > >> > 107092 : users > >> > 6442892 : check-ins > >> > 60.162215665 : average check-ins > >> > no of users : no of check-ins greater than > >> > 17 : >2000 > >> > 244 : >1500 > >> > 475 : >1000 > >> > 1488 : >500 > >> > > >> > Thanks, > >> > Manal > >> > > >> > On Tue, Mar 10, 2015 at 3:48 AM, Matthew Taylor <[email protected]> > >> > wrote: > >> >> > >> >> Manal, > >> >> > >> >> Some questions... > >> >> > >> >> 1. What would you like to get out of NuPIC? Predictions of future > >> >> checkins? Indictions of anomalous behavior? > >> >> 2. Should detected patterns be isolated to each person or detected > >> >> from the population as a whole? > >> >> 3. How often do checkins occur? > >> >> 4. How much past data is available (for training)? > >> >> > >> >> --------- > >> >> Matt Taylor > >> >> OS Community Flag-Bearer > >> >> Numenta > >> >> > >> >> > >> >> On Mon, Mar 9, 2015 at 2:44 PM, Manal Bhingardeve > >> >> <[email protected]> wrote: > >> >> > Hi, > >> >> > > >> >> > I wanted to use CLA to find patterns in user check-ins for location > >> >> > based > >> >> > services. > >> >> > The data consists of check-in details for multiple users with the > >> >> > following > >> >> > fields user_id, check-in time, latitude, longitude, location id. > >> >> > Would the CLA be suited for this kind of an application and if so, > >> >> > could > >> >> > I > >> >> > get some help with the swarming process, more specifically as to > how > >> >> > the > >> >> > geospatial encoder could be used. > >> >> > > >> >> > Thanks, > >> >> > Manal > >> >> > >> > > >> > > > >
