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Answering Keyword Queries involving Aggregates and Group-Bys in Relational Databases

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dc.contributor.author Zhong, ZENG en_US
dc.contributor.author Mong Li, Lee en_US
dc.contributor.author Tok Wang, Ling en_US
dc.date.accessioned 2015-07-13T07:19:24Z en_US
dc.date.accessioned 2017-01-23T06:59:43Z
dc.date.available 2015-07-13T07:19:24Z en_US
dc.date.available 2017-01-23T06:59:43Z
dc.date.issued 2015-07-08 en_US
dc.identifier.uri http://hdl.handle.net/1900.100/5163 en_US
dc.description.abstract Keyword search over relational databases has gained popularity as it provides a user-friendly way to explore structured data. Current research has focused on the computation of minimal units that contain all the query keywords, and largely ignores queries to retrieve statistical information from the database. The latter involves aggregate functions and group-bys, and are called aggregate queries. In this work, we propose a semantic approach to answer keyword queries containing aggregates and group-bys. Our approach utilizes the ORM schema graph to capture the semantics of objects and relationships in the database, and determines the various interpretations of a query. Based on each interpretation, we generate an SQL statement to apply aggregates and group-bys. Further, we detect duplications of objects and relationships arising from denormalized relations so that the aggregate functions will not compute the statistics for the same information repeatedly. Experimental results demonstrate that our approach is able to return correct answers to aggregate queries. en_US
dc.language.iso en en_US
dc.relation.ispartofseries TRA7/15; en_US
dc.title Answering Keyword Queries involving Aggregates and Group-Bys in Relational Databases en_US
dc.type Technical Report en_US

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