Learning knowledge bases for text and multimedia

Knowledge acquisition, representation, and reasoning has been one of the long-standing challenges in artificial intelligence and related application areas. Only in the past few years, massive amounts of structured and semi-structured data that directly or indirectly encode human knowledge became widely available, turning the knowledge representation problems into a computational grand challenge with feasible solutions in sight. The research and development on knowledge bases is becoming a lively fusion area among web information extraction, machine learning, databases and information retrieval, with knowledge over images and multimedia emerging as another new frontier of representation and acquisition. This tutorial aims to present a gentle overview of knowledge bases on text and multimedia, including representation, acquisition, and inference. The content of this tutorial are intended for surveying the field, as well as for educating practitioners and aspiring researchers