Towards Combining Machine Learning with Attribute Exploration for Ontology Refinement Jedrzej Potoniec 1 , Sebastian Rudolph 2 , and Agnieszka  Lawrynowicz 1 1 Institute of Computing Science, Poznan University of Technology, Poland {jpotoniec,alawrynowicz}@cs.put.poznan.pl 2 Technische Universit¨ at Dresden, Germany sebastian.rudolph@tu-dresden.de Abstract. We propose a new method for knowledge acquisition and on- tology refinement for the Semantic Web utilizing Linked Data available through remote SPARQL endpoints. This method is based on combina- tion of the attribute exploration algorithm from formal concept analysis and the active learning approach from machine learning. 1 Introduction Knowledge acquisition is a process of capturing knowledge, typically from a hu- man expert, and thus it concerns all systems and environments where that kind of knowledge is required. It is also said to be major bottleneck in development of intelligent systems due to its difficulty and time requirements. Of course the Semantic Web, as an area concerned with structured and precise representation of information, has to deal with exactly the same issue. Since the early days of the Semantic Web, building ontologies has been a dif- ficult and laborious task. Frequently people trying to express complex knowledge do not know how to perform this task properly. Mistakes come from difficulty in understanding the complex logic formalism supporting OWL. Frequently an ontology engineer would start collecting vocabulary and re- quirements for an ontology, structuralize the vocabulary and later specify more complex dependencies [6]. We propose a solution to support knowledge acquisi- tion for ontology construction. Especially we address the last part of the process, where some basic knowledge is already gathered and more complex dependencies are to be specified. We aim to answer the question how to extend an ontology with meaningful, valid and non-trivial axioms taking into consideration available data and user workload ? 2 Related work For knowledge acquisition for ontology development many approaches have been proposed so far. The most basic ones are ontology editors supporting ontology development, such as Prot´ eg´ e 3 . In addition to that, there are methodologies helpful in ontologies development, such as the one proposed in NeOn [6]. 3 http://protege.stanford.edu/