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The VLDB Journal
Published in: The VLDB Journal 6/2013

01-12-2013 | Regular Paper

YmalDB: exploring relational databases via result-driven recommendations

Authors: Marina Drosou, Evaggelia Pitoura

Published in: The VLDB Journal | Issue 6/2013

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Abstract

The typical user interaction with a database system is through queries. However, many times users do not have a clear understanding of their information needs or the exact content of the database. In this paper, we propose assisting users in database exploration by recommending to them additional items, called Ymal (“You May Also Like”) results, that, although not part of the result of their original query, appear to be highly related to it. Such items are computed based on the most interesting sets of attribute values, called faSets, that appear in the result of the original query. The interestingness of a faSet is defined based on its frequency in the query result and in the database. Database frequency estimations rely on a novel approach of maintaining a set of representative rare faSets. We have implemented our approach and report results regarding both its performance and its usefulness.
previous article Anytime approximation in probabilistic databases

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Metadata
Title
YmalDB: exploring relational databases via result-driven recommendations
Authors
Marina Drosou
Evaggelia Pitoura
Publication date
01-12-2013
Publisher
Springer Berlin Heidelberg
Published in
The VLDB Journal / Issue 6/2013
Print ISSN: 1066-8888
Electronic ISSN: 0949-877X
DOI
https://doi.org/10.1007/s00778-013-0311-4

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