Abstract of the talk: Machines with comprehensive knowledge of the world's entities and their relationships has been a long-standing vision and challenge of AI. In the last decade, huge knowledge bases (aka. knowledge graphs) have been automatically constructed from web data and text sources, and have become a key asset for search, analytics, recommendations and data integration. This digital knowledge can be harnessed to semantically interpret textual phrases in news, social media and web tables, contributing to natural language processing and data analytics.
This talk reviews these advances, discusses recent directions such as acquiring commonsense, and identifies new opportunities and future challenges.
Speaker Bio: Gerhard Weikum is a Scientific Director at the Max Planck Institute for Informatics in Saarbruecken, Germany. His research spans transactional and distributed systems, self-tuning database systems, DB&IR integration, and the automatic construction of knowledge bases. He co-authored a comprehensive textbook on transactional systems, received the VLDB 10-Year Award for his work on automatic DB tuning, and is one of the creators of the YAGO knowledge base. Weikum is an ACM Fellow and a member of several academies in Europe. He has served on various editorial boards and as PC chair of conferences like ACM SIGMOD, ICDE and CIDR. He received the ACM SIGMOD Contributions Award in 2011 and an ERC Synergy Grant in 2013.