Indexing Methods for Sequence Databases
(M. H. Wong)

In real life, data collected day by day often appear in the form of sequences and this form of data is called sequence data. The technique of searching for similar patterns among sequence data is very important in many applications. For example, a scientist may want to find out a certain pattern in the change of temperature at the a financier may want to find certain patterns in the change of GDP and interest rate in order to predict the future economy. The objective of this research is to derive new indexing methods to store sequence data subsequence in a sequence database. The result will benefit the design of he next generation database systems to support scientific and business applications.