Achieving the effectiveness in relation to the relevance of query result is the most crucial part of XML keyword search. Developing an XML Keyword search approach which addresses the user search intention, keyword ambiguity problems and query/search result grading (ranking) problem is still challenging. In this paper, we propose a novel approach called XDMA for keyword search in XML databases that builds two indices to resolve these problems. Then, a keyword search technique based on two-level matching between two indices is presented. Further, by utilizing the logarithmic and probability functions, a terminology that defines the Mutual Score to find the desired T-typed node is put forward. We also introduce the similarity measure to retrieve the exact data through the selected T-typed node. In addition, grading for the query results having comparable relevance scores is employed. Finally, we demonstrate the effectiveness of our proposed approach, XDMA with a comprehensive experimental evaluation using the datasets of DBLP, WSU and eBay.
Comparison of XReal and XDMA for Keyword Search in XML Databases: A Case Study