https://www.woasjournals.com/index.php/ijitas/issue/feed 2022-06-01T10:02:38+00:00 IJITAS Journal contact@woasjournals.com Open Journal Systems <p><strong>International Journal of Information Technology and Applied Sciences (IJITAS) -ISSN 2709-2208 (Online)-</strong> is a peer-reviewed International Journal that currently publishes 4 issues annually. IJITAS is published by the <a href="http://www.woasjournals.com/" target="_blank" rel="noopener">World Organization of Applied Sciences (WOAS)</a>. IJITAS journal publishes technical papers, as well as review articles and surveys, describing recent research and development work that covers all areas of computer science, information systems, and computer / electrical engineering.</p> <p align="justify"><em><strong>Cross Reference</strong></em></p> <p align="justify"><strong>International Journal of Information Technology and Applied Sciences (IJITAS)</strong> is a member of the <strong>CrossRef. </strong>The DOI prefix allotted for IJITAS is <a href="https://doi.org/10.52502/ijitas"><strong>10.52502/ijitas</strong></a></p> https://www.woasjournals.com/index.php/ijitas/article/view/269 2022-05-30T22:45:46+00:00 Sakib Rahman sakibrahman.11.27@gmail.com Nafis Anim nianim2238@gmail.com SARKER TANVEER AHMED RUMEE rumee@cse.du.ac.bd

<p>Searching educational and research content has been made easier by popular online repositories such as NCBI, google scholar, etc. For a user query, they generally return thousands of results and also rank them. However, these tools often produce results that are distantly related to user query goals and often overwhelm the users with the volume of results. In recent years, researchers are experimenting with content-specific databases and thereby producing few but more relevant query results. This project creates an exact snapshot of the PubMed database from NCBI and provides users with novel search options that sort and display the results on the basis of matching percentages between query keywords and article titles. The proposed system uses Natural Language Processing (NLP) techniques to aid users to form search queries in plain English that would otherwise only be possible through setting up advanced search options. The experiment results were promising and found to produce more relevant query results compared to the state-of-the-art methods.</p>

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