Abstract. Most approaches to information filtering taken so far have the underlying hypothesis of potentially delivering notifications from every information producer to subscrib...
Christian Zimmer, Christos Tryfonopoulos, Klaus Be...
Sampling is a widely used technique to increase efficiency in database and data mining applications operating on large dataset. In this paper we present a scalable sampling imple...
In this paper, we present a case study for the visualisation and analysis of large and complex temporal multivariate networks derived from the Internet Movie DataBase (IMDB). Our ...
Adel Ahmed, Vladimir Batagelj, Xiaoyan Fu, Seok-He...
Abstract--Until quite recently, extending Phrase-based Statistical Machine Translation (PBSMT) with syntactic knowledge caused system performance to deteriorate. The most recent su...
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...