It is widely known that there a lot of useful information hidden in big data, leading to new saying "data money." Thus, it prevalent for individuals mine crucial utilization many real-world applications. In the past, studies have considered frequency. Unfortunately, doing so neglects other aspects, such as utility, interest, or risk. sensible discover high-utility itemsets (HUIs) transaction da...

Description Logic Programs (DLP) is an expressive but tractable subset of OWL. In this paper, we study a rising but under-researched problem of learning DLP from uncertain data. Current research rarely explores the plentiful uncertain data populating the Semantic Web. We handle uncertain data in Inductive Logic Programming (ILP) framework by modifying the performance evaluation criteria. We ado...

In practice, we often come across situations where it is necessary to make decisions based on incomplete or uncertain data. In control systems it may be due to the unknown exact mathematical model, or its excessive complexity (e.g. nonlinearity) when it is necessary to simplify it, respectively, to solve it using a rule base. In the case of databases, searching data we compare a similarity meas...