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The VLDB Journal

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01.12.2013 | Regular Paper

YmalDB: exploring relational databases via result-driven recommendations

verfasst von: Marina Drosou, Evaggelia Pitoura

Erschienen in: The VLDB Journal | Ausgabe 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.

Vorheriger Artikel Anytime approximation in probabilistic databases

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Titel: YmalDB: exploring relational databases via result-driven recommendations
verfasst von: Marina Drosou
Evaggelia Pitoura
Publikationsdatum: 01.12.2013
Verlag: Springer Berlin Heidelberg
Erschienen in: The VLDB Journal / Ausgabe 6/2013
Print ISSN: 1066-8888
Elektronische ISSN: 0949-877X
DOI: https://doi.org/10.1007/s00778-013-0311-4

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