Temporal Keyword Search with Aggregates and Group-By
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Abstract. Temporal keyword search enables non-expert users to query temporal relational databases with time conditions. However, aggregates and group-by are currently not supported in temporal keyword search, which hinders querying of statistical information in temporal databases. This work proposes a framework to support aggregate, group-by and time condition in temporal keyword search. We observe that simply combining non-temporal keyword search with aggregates, group-by, and temporal aggregate operators may lead to incorrect and meaningless results as a result of data duplication over time periods. As such, our framework utilizes Object-Relationship-Attribute semantics to identify a unique at-tribute set in the join sequence relation and remove data duplicates from this attribute set to ensure the correctness of aggregate and group-by computation. We also consider the time period in which temporal at-tributes occur when computing aggregate to return meaningful results. Experiment results demonstrate the importance of these steps to retrieve correct results for keyword queries over temporal databases.
Temporal Keyword Search, Aggregates and Group-By, Se-mantic Approach