Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
Social networks have recently garnered considerable interest. With the intention of utilizing social networks for the Semantic Web, several studies have examined automatic extract...
We present a novel approach to discovering relations and their instantiations from a collection of documents in a single domain. Our approach learns relation types by exploiting m...
Harr Chen, Edward Benson, Tahira Naseem, Regina Ba...
Abstract. Clustering is often considered the most important unsupervised learning problem and several clustering algorithms have been proposed over the years. Many of these algorit...
An important problem that arises during the data mining process in many new emerging application domains is mining data with temporal dependencies. One such application domain is a...