This is one of the scenarios that can be handled using CEP (Complex
Event Processing) - basically rule logic with some extensions to make
time based reasoning more convenient. In Drools, you have @event
to declare a fact type as an event type, temporal operators to
establish temporal relations between events, "windows" to select
recently arrived subsets of facts, etc. Much depends on whether you
need to handle this in real time or whether it's going to be handled
over a bulk of historic data.
All my hints on mapping facts to days are useless - you may have to
use floating intervals or an approach that's triggered by the first
smell of a certain "crime"...
-W
On 18/06/2014, naresh.t <nareshthota005(a)gmail.com> wrote:
Dear Wolfgang, Thanks for your patience and understandings.
Let me clear our requirement. Actually we are not working any student
psychology thing. I thought to simplify the problem in terms of Student
example but it is getting complicated.
What we are trying to achieve is...
We have some RAW logs(windows event logs like login success, login failed,
bad user name and password etc., along with date and time) in our DB.
We are trying get trend of some particular events like bad user name and
password. If these type of events are happening in less span of time, then
we will find those user names and do some activity on them.
In our existing application, we have achieved this by using java with hard
coded inputs. Means we are getting those events, if any 5 events occurred
in
3 minutes.
Now we are trying to add some dynamism for these type of requirements. We
are exploring Drools Rule Engines to check that is it compatible with these
type of rules. If you have any other Rule Engines in your mind, please
suggest us.
Thanks
Naresh
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