Abstract:
Mining data from text is often becomes a crucial part of data mining tasks. With the
growing tendency of using cloud and sharing more and more les over the internet, the
necessity of applying a string matching algorithm in text mining has increased rapidly in
present time. In recent years many pattern matching algorithms are proposed to enhance
information retrieval from large le(s), especially in search engines as a mean of searching
a certain term throughout multiple web pages to rank pages. These tasks require a faster
string matching that can nd a certain pattern from a text with a very minimal waste of
time. This can be ensured by using an algorithm that makes less character comparisons
and pattern shifts while searching. In this paper, we're proposing a new algorithm named
Back and Forth Matching (BFM) algorithm to perform string matching tasks in faster
way by matching a pattern from both the forward and backward direction. A comparison
of this algorithm with other algorithm shows a tremendous improvement in matching
strings in large text les. For this advantage, we have implemented this algorithm in
searching through universities course curriculum in Bangladesh context and compare it
with the existing job circulars, in order to nd out how much the university curriculum
is relevant with respect to current job markets. This will provide universities to learn
about their laggings and thereby make necessary improvements as per the suggestions
generated from our project.
