Top (k1,k2) Query in Uncertain Datasets

In this letter, we propose a novel kind of uncertain query, top (k1,k2) query. The x-tuple model and the possible world semantics are used to describe data objects in uncertain datasets. The top (k1,k2) query is going to find k2 x-tuples with largest probabilities to be the result of top k1 query in...

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Bibliographic Details
Published inIEICE Transactions on Information and Systems Vol. E98.D; no. 11; pp. 1998 - 2002
Main Authors LIU, Fei, LIN, Jiarun, JIA, Yan
Format Journal Article
LanguageEnglish
Published The Institute of Electronics, Information and Communication Engineers 2015
Subjects
possible world
top k
uncertain query
x-tuple
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Summary:In this letter, we propose a novel kind of uncertain query, top (k1,k2) query. The x-tuple model and the possible world semantics are used to describe data objects in uncertain datasets. The top (k1,k2) query is going to find k2 x-tuples with largest probabilities to be the result of top k1 query in a possible world. Firstly, we design a basic algorithm for top (k1,k2) query based on dynamic programming. And then some pruning strategies are designed to improve its efficiency. An improved initialization method is proposed for further acceleration. Experiments in real and synthetic datasets prove the performance of our methods.
ISSN:0916-8532
1745-1361
DOI:10.1587/transinf.2015EDL8077