Abstract:
Word shortlisting simply refers to shortening the list. Shortlisting of curriculum vitaes is very
time consuming and abstract work. There are number of software tools that can detect and
shortlist resumes. Almost all of these tools are available for English language, but similar
tools for Sinhala language is not yet available.
There are many attempts of developing language dependent shortlisting tools for languages
like Hindi, Chinese, French, Malayalam, Arabic, and English. Most of these tools
outperforms the available language independent commercial shortlisting tools as well.
Sinhala language being similar to these languages and also being the official language of Sri
Lanka along with Tamil, the need of a comprehensive tool to reduce the time for the
recruitment procedure is a timely need. Due to the complexity of the language itself the
available language independent tools produces very poor results.
This research’s main objective is to address the need of a classification tool for Sinhala
language to detect and identify similarity of words and rank them according to the weight. A
novel algorithm has been developed to detect words correctly and to preprocess then rank then
corerctly. The proposed system mainly consists of two stages as text pre-processing and
classifying (ranking). Sinhala language resources used in this project were taken from the
Language Technology Research Laboratory of University of Colombo and Natural Language
Processing Research group of University of Kelaniya. Testing and validations has been carried
out by collecting random text samples govenement organizations.
