An ontology-based approach for semantics ranking of the web search engines results

TL;DR

This paper introduces a semantic web approach to evaluate and rank search engine results more effectively by considering the meaning behind queries and documents, aiming to enhance relevance and performance.

Contribution

It proposes a novel ontology-based semantic evaluation method for search engines, improving result relevance and evaluation accuracy.

Findings

Semantic evaluation improves search result relevance

The approach is applicable to real search engines

Semantic ranking enhances search performance

Abstract

This work falls in the areas of information retrieval and semantic web, and aims to improve the evaluation of web search tools. Indeed, the huge number of information on the web as well as the growth of new inexperienced users creates new challenges for information retrieval; certainly the current search engines (such as Google, Bing and Yahoo) offer an efficient way to browse the web content. However, this type of tool does not take into account the semantic driven by the query terms and document words. This paper proposes a new semantic based approach for the evaluation of information retrieval systems; the goal is to increase the selectivity of search tools and to improve how these tools are evaluated. The test of the proposed approach for the evaluation of search engines has proved its applicability to real search tools. The results showed that semantic evaluation is a promising way to improve the performance and behavior of search engines as well as the relevance of the results that they return.