This paper presents a semantic-aware classification algorithm that can leverage the interoperability among semantically heterogeneous learning object repositories using different ...
Ming-Che Lee, Kun Hua Tsai, Tung Cheng Hsieh, Ti K...
We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy, but may behave di erently due to position-dependent inputs. All...
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...
Ontology Learning from text aims at generating domain ontologies from textual resources by applying natural language processing and machine learning techniques. It is inherent in t...
Our shared belief is that learning, like other human activities, cannot and will not be confined within rigidly defined course systems or learning repositories, inclosing learning...
Mohamed Amine Chatti, Ralf Klamma, Christoph Quix,...