  Many new database application domains such as experimental sciences and
medicine are characterized by large sequences as their main form of data. Using
approximate representation can significantly reduce the required storage and
search space. A good choice of representation, can support a broad new class of
approximate queries, needed in these domains. These queries are concerned with
application dependent features of the data as opposed to the actual sampled
points. We introduce a new notion of generalized approximate queries and a
general divide and conquer approach that supports them. This approach uses
families of real-valued functions as an approximate representation. We present
an algorithm for realizing our technique, and the results of applying it to
medical cardiology data.
  (Extended version is available in Tech Report CS-95-03, Dept of Computer
Science, Brown University.
http://cs.brown.edu/research/pubs/techreports/reports/CS-95-03.html)
