A semantic approach to keyword search over relational databases

Research in relational keyword search has been focused on the efficient computation of results from multiple tuples as well as strategies to rank and output the most relevant ones. However, the challenge to retrieve the intended meaningful results remains. Existing relational keyword search techniques suffer from the problem of returning many incomplete results. In this work, we adopt a semantic approach to relational keyword search via an Object-Relationship-Mixed graph (ORMgraph). This graph is constructed based on database schema constraints to capture the semantics of objects and relationships in the data. Each node in the ORM-graph represents either an object, or a relationship, or both. We design an algorithm that utilizes the ORM-graph to process keyword queries. Experiment results show our approach returns more complete and meaningful results compared to existing methods, and is efficient.