A SURVEY ON SEMANTIC SEARCH TECHNIQUE

Abstract

Semantic search is thought as a series of activities and techniques to boost the search accuracy by clearly
understanding users’ search intent. Usually, linguistics search engines needs metaphysics and linguistics information to
research user queries. However, building a selected metaphysics and linguistics information supposed for big amounts of
information could be a terribly time intense and expensive task. so as to resolve this downside, we have a tendency to
propose a unique linguistics search technique that doesn't need ontologies and linguistics information by taking
advantage of semantically enriched text model. Through in depth experiments victimisation the OSHUMED document
assortment and SCOPUS library information, we have a tendency to show that our planned technique improves users’
search satisfaction.