Using Page Size for Controlling Duplicate Query Results in Semantic Web

TL;DR

This paper proposes a new algorithm combining hash index and page size comparisons to effectively detect and eliminate duplicate query results in the semantic web, addressing limitations of existing hash-based methods.

Contribution

It introduces a novel duplicate detection algorithm that improves accuracy and can be integrated into existing SQL-based semantic web query systems.

Findings

Efficient removal of duplicate results demonstrated in experiments.

Overcomes hash index limitations with a combined approach.

Compatible with current SQL-based systems.

Abstract

Semantic web is a web of future. The Resource Description Framework (RDF) is a language to represent resources in the World Wide Web. When these resources are queried the problem of duplicate query results occurs. The present techniques used hash index comparison to remove duplicate query results. The major drawback of using the hash index to remove duplicate query results is that, if there is a slight change in formatting or word order, then hash index is changed and query results are no more considered as duplicate even though they have same contents. We presented an algorithm for detection and elimination of duplicate query results from semantic web using hash index and page size comparisons. Experimental results showed that the proposed technique removed duplicate query results from semantic web efficiently, solved the problems of using hash index for duplicate handling and could be embedded in existing SQL-Based query system for semantic web. Research could be carried out for certain flexibilities in existing SQL-Based query system of semantic web to accommodate other duplicate detection techniques as well.