Scientific and technical information's restoration in the open access environment through smart search engines

Abstract

Open access is one of the topics that attracted the researchers interest as it is a turning point for the recovery of technical and scientific information’s recovery which requires a set of tools and technical skills. This study aims to discover the main problems of information’s recovery within open access in addition to the inventory of the most important smart search engines and to know the strategies of information’s recovery. The study adopted the descriptive analytical approach, and came out with a number of important conclusions, the most important are : Searching for scientific and technical information in the open access environment has become a very difficult and the researcher does not know which of them is more useful. Relying on the common ranking of sites, smart search engines in its work, depends on semantic web applications, most notably XML, RDF and ontology, users can quickly find specific search results through smart search engines without having to become experts in search engines or have a well-defined strategies for searching within the open access environment. The study also showed that the semantic scholar search engine deals with open sources more efficiently than traditional search engines through its ability to discover these sources and display them to the beneficiary in a distinctive way.