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The authors propose in this paper an interactive query recommendation system, namely FIMIOQR. It is designed to help OLAP (On-Line Analytical Processing) users in their decision query writing task based on both a set of selected measures and decision queries log file. Their FIMIOQR system is designed to discover associations from decision queries log file. For this end, they use association rules method to extract frequent item-sets from dimensions attributes according to user selected set of measures. This allows end users in OLAP systems to write relevant queries guided by an interactive recommending system and helps them to meet their analysis objectives.
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