Abstract
Research in relational keyword search has been focused on the efficient computation of results as well as strategies to rank and output the most relevant ones. However, the challenge to retrieve the intended results remains. Existing relational keyword search techniques suffer from the problem of returning overwhelming number of results, many of which may not be useful. In this work, we adopt a semantic approach to relational keyword search via an Object-Relationship-Mixed data graph. 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 data graph represents either an object, or a relationship, or both. We design an algorithm that utilizes the ORM data graph to process keyword queries. Experiment results show our approach returns more informative results compared to existing methods, and is efficient.
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Zeng, Z., Bao, Z., Lee, M.L., Ling, T.W. (2013). A Semantic Approach to Keyword Search over Relational Databases. In: Ng, W., Storey, V.C., Trujillo, J.C. (eds) Conceptual Modeling. ER 2013. Lecture Notes in Computer Science, vol 8217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41924-9_21
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DOI: https://doi.org/10.1007/978-3-642-41924-9_21
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