Search Engines: A Systematic Review

  • Honey Talreja, Pranav Shirude, Shrirang Mhalgi, Ria Mittal, Laxmi Bewoor

Abstract

The current scenario of ever increasing information is rapidly progressing and demands a much efficient way of storage, organization and retrieval of information. Search engine organizations continuously refine their search algorithms to improve user experience. Most search engines extract results based on keywords. Sometimes the search engine fails to identify the correct keywords and may deliver irrelevant results which do not cater the user’s needs. The extracted results are arranged using dynamic page ranking algorithms which are based on various factors including user’s feedback. Thus, there is a scope of improvement for getting concrete results by using better machine learning algorithms and NLP techniques for keyword recognition. The proposed system aspires to deliver relevant results based on Deep Semantic Understanding of the query administered by the end user.

Published
2020-03-19
How to Cite
Ria Mittal, Laxmi Bewoor, H. T. P. S. S. M. (2020). Search Engines: A Systematic Review. International Journal of Advanced Science and Technology, 29(4s), 1134 - 1141. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/6665