Abstract
Querying temporal relational databases is a challenge for non-expert database users, since it requires users to understand the semantics of the database and apply temporal joins as well as temporal conditions correctly in SQL statements. Traditional keyword search approaches are not directly applicable to temporal relational databases since they treat time-related keywords as tuple values and do not consider the temporal joins between relations, which leads to missing answers, incorrect answers and missing query interpretations. In this work, we extend keyword queries to allow the temporal predicates, and design a schema graph approach based on the Object-Relationship-Attribute (ORA) semantics. This approach enables us to identify temporal attributes of objects/relationships and infer the target temporal data of temporal predicates, thus improving the completeness and correctness of temporal keyword search and capturing the various possible interpretations of temporal keyword queries. We also propose a two-level ranking scheme for the different interpretations of a temporal query, and develop a prototype system to support interactive keyword search.
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Gao, Q., Lee, M.L., Ling, T.W., Dobbie, G., Zeng, Z. (2018). Analyzing Temporal Keyword Queries for Interactive Search over Temporal Databases. In: Hartmann, S., Ma, H., Hameurlain, A., Pernul, G., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2018. Lecture Notes in Computer Science(), vol 11029. Springer, Cham. https://doi.org/10.1007/978-3-319-98809-2_22
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DOI: https://doi.org/10.1007/978-3-319-98809-2_22
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