Nowadays there are a large number of XML documents on the web. This means that information retrieval techniques for searching XML documents are very important and necessary for internet users. Moreover, it is often said that users of search engines want to browse only relevant content in each document. Therefore, an effective XML element search aims to produce only the relevant elements or portions of an XML document. Based on the demand by users, the purpose of this paper is to propose and evaluate a method for obtaining more accurate search results in XML search.

The existing approaches generate a ranked list in descending order of each XML element's relevance to a search query; however, these approaches often extract irrelevant XML elements and overlook more relevant elements. To address these problems, the authors' approach extracts the relevant XML elements by considering the size of the elements and the relationships between the elements. Next, the authors score the XML elements to generate a refined ranked list. For scoring, the authors rank high the XML elements that are the most relevant to the user's information needs. In particular, each XML element is scored using the statistics of its descendant and ancestor XML elements.

The experimental evaluations show that the proposed method outperforms BM25E, a conventional approach, which neither reconstructs XML elements nor uses descendant and ancestor statistics. As a result, the authors found that the accuracy of an XML element search can be improved by reconstructing the XML elements and emphasizing the informative ones by applying the statistics of the descendant XML elements.

This work focused on the effectiveness of XML element search and the authors did not consider the search efficiency in this paper. One of the authors' next challenges is to reduce search time.

The paper proposes a method for improving the effectiveness of XML element search.