Top-k keyword search with recursive semantics in relational databases

Abstract

Existing solutions for keyword search over relational databases focused on finding joined tuple structures from a data graph. We observe that such a graph using tuples as nodes and foreign-key references as edges cannot describe the joining connections between tuples within a single relation, and thus cannot support recursive query semantics over a relational database. To solve this problem, in our approach, we firstly model a weighted data graph considering both foreign key references and tuple joining connections within a single relation. Secondly, we discuss the ranking strategy for both nodes and edges supporting the recursive semantics by incorporating PageRank methods. Finally, an approximation algorithm as well as a top-k enumeration algorithm is presented by running Dijkstra algorithm based on dynamic programming strategy to enumerate result tuple trees. At the end of this paper, we conduct an experimental study and report the findings.