1) A Spatiotemporal data stream contains information which changes over time, and is in the form of stream data (i.e., the data flow in and out like possible infinite streams).
a) Write down three application examples of spatiotemporal data mining.
b) Identify and explain the main challenges in spatiotemporal data mining.
c) Using one application example, sketch a method to mine one type of knowledge from such stream data efficiently.
2)Assume that data for analysis includes the attribute age. The age values for the data tuples are 13, 15, 16, 16, 19, 20, 20, 21, 22, 22, 25, 25, 25, 25, 30, 33, 33, 35, 35, 35, 35, 36, 40, 45, 46, 52, 70.
a) Use smoothing by bin means to smooth data, using bin depth of 3. Demonstrate your steps.
b) How might you find out outliers in the data?
c) What other methods are there for data smoothing.
3) In Data ware house technology, a multiple dimensional view can be implemented by a relational database technique (ROLAP), or by a multidimensional database technique (MOLAP) or by a hybrid database technique (HOLAP)
a) Briefly explain each implementation technique.
b) For one technique, describe how each of the following functions may be implemented.
(i) The generation of a data ware house.
(ii) Roll-up and Drilldown
(iii) Incremental updating