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With the amount of available information on the Web growing rapidly with each day, the need to automatically filter the information in order to ensure greater user efficiency has emerged. Within the fields of user profiling and Web personalization several popular content filtering techniques have been developed. In this chapter we present one of such(More)
Subgroup discovery aims at constructing symbolic rules that describe statistically interesting subsets of instances with a chosen property of interest. Semantic subgroup discovery extends standard subgroup discovery approaches by exploiting ontological concepts in rule construction. Compared to previously developed semantic data mining systems SDM-SEGS and(More)
We present experimental results of confronting the k-Nearest Neighbor (kNN) algorithm with Support Vector Machine (SVM) in the collaborative filtering framework using datasets with different properties. While k-Nearest Neighbor is usually used for the collaborative filtering tasks, Support Vector Machine is considered a state-of-the-art classification(More)
Today, we can observe a number of emerging trends in technologies for intelligent knowledge access, including search engines, categorisation tools and visualisation systems. This paper gives a brief overview of them, describes ongoing efforts to develop Semantic Web-based knowledge access tools and discusses how a semantic web-based approach can provide a(More)
Many data mining techniques are these days in use for ontology learning – text mining, Web mining, graph mining, link analysis, relational data mining, and so on. In the current state-of-the-art bundle there is a lack of " software mining " techniques. This term denotes the process of extracting knowledge out of source code. In this paper we approach the(More)
Keywords : Predictive sentiment analysis Stream-based active learning Stock market Twitter Positive sentiment probability Granger causality a b s t r a c t Studying the relationship between public sentiment and stock prices has been the focus of several studies. This paper analyzes whether the sentiment expressed in Twitter feeds , which discuss selected(More)
Geospatial Web services allow to access and to process Geospatial data. Despite significant standardisation efforts, severe heterogeneity and inter-operability problems remain. The SWING environment 1 leverages the Semantic Web Services (SWS) paradigm to address these problems. The environment supports the entire life-cycle of Geospatial SWS. To this end,(More)