Meaningful Interrelated Object Tree for XML keyword search

In the research field of XML retrieval with keyword-based approach, a variant of Lowest Common Ancestors (LCAs) have been widely accepted to provide how keywords are connected by ancestor relationship. However, returning a whole subtree or a partial subtree based on LCA nodes is insufficient for identifying how subtrees are conceptually related under different tree structure such as ID/IDREF. On the other hand, storing XML documents in the graph model can define richer relationships that the tree model cannot but the cost of enumerating result is very high. In this paper, we propose a novel Smallest Lowest Object Tree (SLOT) which keywords are connected through physical connections. In addition, to capture conceptual connections, we also propose the Smallest Interrelated Object Tree (SIOT) which extends ID/IDREF relationships based on SLOT. Finally, our experiment indicates that the proposed approach returns more effective and more semantic results for users.