Temprora: Top-K Temporal-Probabilistic Results Analysis

2016 IEEE 32nd International Conference on Data Engineering (ICDE)(2016)

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摘要
The study of time and probability, as two combined dimensions in database systems, has focused on the correct and efficient computation of the probabilities and time intervals. However, there is a lack of analytical information that allows users to understand and tune the probability of time-varying result tuples.In this demonstration, we present TemProRA, a system that focuses on the analysis of the top-k temporal probabilistic results of a query. We propose the Temporal Probabilistic Lineage Tree (TPLT), the Temporal Probabilistic Bubble Chart (TPBC) and the Temporal Probabilistic Column Chart (TPCC): for each output tuple these three tools are created to provide the user with the most important information to systematically modify the time-varying probability of result tuples. The effectiveness and usefulness of TemProRA are demonstrated through queries performed on a dataset created based on data from Migros, the leading Swiss supermarket branch.
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关键词
TemProRA,top-k temporal-probabilistic results analysis,database systems,time-varying result tuple probability,query,temporal probabilistic lineage tree,TPLT,temporal probabilistic bubble chart,TPBC,temporal probabilistic column chart,TPCC,Migros,Swiss supermarket branch
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