We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
We consider the problem of nding rules relating patterns in a time series to other patterns in that series, or patterns in one series to patterns in another series. A simple examp...
Gautam Das, King-Ip Lin, Heikki Mannila, Gopal Ren...
As programs evolve, newly added functionality sometimes no longer aligns with the original design, ending up scattered across the software system. Aspect mining tries to identify ...
Abstract. We present a technique for discovering and representing changes between versions of data warehouse structures. We select a tree comparison algorithm, adapt it for the par...
Abstract—Change prediction helps developers by recommending program entities that will have to be changed alongside the entities currently being changed. To evaluate their accura...