Keywords are useful tools as they give the shorter summary of the
document. Keywords are useful for a variety of purposes including
summarizing, indexing, labeling, categorization, clustering, and searching, and
in this paper we will use keywords in order to find the relevance degree
between an English text and its title.
The proposed system solves this problem through simple statistic (Term
frequency) and linguistic approaches by extracting the keywords of the title
and keywords of the text (with their frequency that appear in the text) and
finding the average of title's keywords frequency across the text that represent
the relevance degree that required, with depending on a lexicon of a particular
field(in this work we choose computer science field). This lexicon is
represented using two different B+ trees one for non-keywords and the other
for candidate keywords, these keywords was stored in a manner that prevent
redundancy of these terms or even sub-terms to provide efficient memory
usage and to minimize the search time.
The proposed system was implemented using Visual Prolog 5.1 and after
testing, it proved to be valuable for finding the degree of relevance between a
text and its title (from point of view of accuracy and search time).