This paper proposes a contextual preference query method of XML structural relaxation and content scoring to resolve the problem of empty or too many answers returned by XML. This paper proposes a XML contextual preference (XCP) model, where all the possible relaxing queries are determined by the users’ preferences. The XCP model allows users to express their interests on XML tree nodes, and then users assign interest scores to their interesting nodes for providing the best answers. A preference query results ranking method is proposed based on the XCP model, which includes: a Clusters_Merging algorithm to merge clusters based on the similarity of the context states, a Finding_Orders algorithm to find representative orders of the clusters, and a Top-k ranking algorithm to deal with the many answers problem. Results of preliminary user studies demonstrate that the method can provide users with most relevant and ranked query results. The efficiency and effectiveness of the approach are also demonstrated by experimental results.
Skyline Preference Query Based on Massive and Incomplete Dataset
