PROJECT TITLE :

Top-Down XML Keyword Query Processing

ABSTRACT:

Efficiently answering XML keyword queries has attracted abundant research effort within the last decade. The key factors ensuing within the inefficiency of existing strategies are the common-ancestor-repetition (CAR) and visiting-useless-nodes (VUN) problems. To handle the CAR downside, we propose a generic prime-down processing strategy to answer a given keyword query w.r.t. LCA/SLCA/ELCA semantics. By “top-down”, we have a tendency to mean that we tend to visit all common ancestor (CA) nodes in an exceedingly depth-1st, left-to-right order; by “generic”, we tend to mean that our method is freelance of the question semantics. To handle the VUN downside, we tend to propose to use kid nodes, instead of descendant nodes to check the satisfiability of a node w.r.t. the given semantics. We propose two algorithms that are based mostly on either ancient inverted lists or our newly proposed LLists to enhance the performance. We tend to further propose several algorithms that are primarily based on hash search to simplify the operation of finding CA nodes from all concerned LLists. The experimental results verify the advantages of our strategies per varied evaluation metrics.