Data mining is a widely used technology for various real-life applications of data analytics and important to discover valuable association rules in transaction databases. Interesting itemset plays an role many applications, such as market, e-commerce, finance, medical treatment. To date, algorithms based on frequent patterns have been studied, but there are few that focus infrequent or rare pa...

Many applications of the semantic web and Web 2.0 aim to empower the knowledge worker. These applications however, do not allow the user to combine all of his/her social and semantic information into a single resource which allows data to be processed, managed and enhanced automatically. In our demo we will present a number of demo applications based on Galaxy, IBM’s ontological network miner, ...

Process Mining attempts to reconstruct the workflow of a business process from logs of activities. This task is quite important in business scenarios where there is not a well understood and structured definition of the business process performed by workers. Activities logs are thus mined in the attempt to reconstruct the actual business process. In this paper, we propose the generalization of ...

Inductive databases are a new generation of databases, that are capable of dealing with data but also with patterns or regularities within the data. A user can generate, manipulate and search for patterns of interest using an inductive query language. Data mining then becomes an interactive querying process. The inductive database framework is especially interesting for bioand chemoinformatics,...

UNLABELLED Birth weight can be a predictor of maternal health issues related to nutrition and environmental contaminants. Total hair mercury (HHg) concentration was studied as an indicator of both fish consumption and methylmercury exposure in mothers (and newborns) living in selected low income areas of the Madeira River basin, Amazonia, Brazil. This cohort study (n = 1,433) consisted of tradi...

Given a collection of boolean spatial features, the co-location pattern discovery process nds the subsets of features frequently located together. For example, the analysis of an ecology dataset may reveal the frequent co-location of a re ignition source feature with a needle vegetation type feature and a drought feature. The spatial co-location rule problem is diierent from the association rul...

Bácsi, K., Kósa, JP., Balla, B., Lazáry, Á., Nagy, Z., Takács, I., Speer, G., Lakatos, P. Decreasedactivity of lactase phlorizin hydrolase and bone mineral densityin postmenopausal women. American Society for Bone and Mineral Research (ASBMR)29th Annual Meeting Honolulu, HI, USA September 16-19, 2007. J Bone Miner Res2007, 22(S1): S186 Bácsi, K., Kósa, JP., Balla, B., Lazáry, Á....