1 Introduction Conventional relatio

1 Introduction
Conventional relational databases were designed to
capture a snapshot of reality. Although such databases
well serve many applications which need only the most
recent data, they are insufficient for those which need to
retrieve past as well as current data. We call such
databases temporal databases which are capable of
storing and retrieving time dependent data [1−4].
Many researchers have proposed various temporal
data models to utilize relational technologies. Among
them, an interval-based temporal data model is popular
because the data model can be easily implemented on top
of an existing relational database by simply adding two
additional attributes for intervals. Despite its fast
utilization of relational databases, such a data model
represents a real world entity in multiple tuples, which
requires combining scattered tuples for an entity for a
query. Moreover, it uses intervals as timestamps which
are not closed under set theoretic operations, leading to
the increase of query language complexity