In this paper, we study different database optimization
techniques that can be employed for novelty detection, which
is the process of singling out novel information from a given
set of text documents [7]. In today’s life, information is
brought in at an escalating rate, such as in news, blogs [2],
forums, and social networks [13]. As such, repeated
information arising from competition of various companies or
firms can often make our searches longer due to redundancy
[6]. However, the research on novelty detection [12], [14],
[15], [16] comes hand in hand with a database system.
Therefore, in this paper, we used a novelty detection
application implemented in C++ [5], a programming
application that is tied together with a database.