Element Retrieval using Namespace Based on keyword search over XML Documents

TL;DR

This paper introduces a namespace-based semantic similarity algorithm for XML element retrieval that improves accuracy and reduces computation time by considering semantic information in element namespaces.

Contribution

The paper proposes a novel algorithm that leverages namespace semantic information for efficient and accurate XML element retrieval, addressing limitations of existing similarity measures.

Findings

Improved query accuracy over traditional methods

Reduced running time in XML element search

Effective use of semantic namespace information

Abstract

Querying over XML elements using keyword search is steadily gaining popularity. The traditional similarity measure is widely employed in order to effectively retrieve various XML documents. A number of authors have already proposed different similarity-measure methods that take advantage of the structure and content of XML documents. They do not, however, consider the similarity between latent semantic information of element texts and that of keywords in a query. Although many algorithms on XML element search are available, some of them have the high computational complexity due to searching a huge number of elements. In this paper, we propose a new algorithm that makes use of the semantic similarity between elements instead of between entire XML documents, considering not only the structure and content of an XML document, but also semantic information of namespaces in elements. We compare our algorithm with the three other algorithms by testing on the real datasets. The experiments have demonstrated that our proposed method is able to improve the query accuracy, as well as to reduce the running time.