Recommenders are central in current applications to help the user find useful information spread in large amounts of data. Most Recommenders are more effective when huge amounts of user data are available in order to ...

Based on three versions of a small macroeconomic model for Brazil, this paper presents empirical evidence on the effects of parameter uncertainty on monetary policy rules and on the robustness of optimal and simple rules ...

Association rule mining is an important data mining technique used for discovering relationships among all data items. Membership functions have a significant impact on the outcome of the mining association rules. An ...

Association rules are widely used to find relations among items in a given database. However, the amount of generated rules is too large to be manually explored. Traditionally, this task is done by post-processing approaches ...

This article is motivated by the prominence of one-sided S,s rules in the literature and by the unrealistic strict conditions necessary for their optimality. It aims to assess whether one-sided pricing rules could be an ...

The correct automatic pronunciation of words is a nontrivial problem, even for inflexions of Portuguese verbs, and has not been systematically solved yet, if verbal irregularity is taken into account. The purpose of this ...

Large growing knowledge bases have been an interesting field in many researches in the past few years. Most techniques focus on constructing algorithms to help a Knowledge Base (KB) automatically (or semi automatically) ...

This article is motivated by the prominence of one-sided S,s rules in the literature and by the unrealistic strict conditions necessary for their optimality. IT aims to assess whether one-sided pricing rules could be an ...

Active database systems integrate event-based rule processing with traditional database functionality. The model most widely used to represent event-based rules is the Event- Condition-Action rule (ECA rule) model. However, ...