Talk: AI Meets Society: responsibly designing smart systems & infrastructures, 19th September 2019, Zug, Swiss
Trust is not necessarily about Transparency, but about Interaction. In current times: Industrialization was/is all about gaining more efficiency and productivity; Digital platforms target attention spans and the predictive behaviour, trying to maximize engagement for profits – sure that shall…
Talk & Panel: Responsible AI: Trust, Fairness, and Transparency in Machine Learning at the appliedAI Ecosystem Meetup in Munich, 14. January 2019
Around 150 attendees participated in the appliedAI Ecosystem Meetup on Artificial Intelligence in Munich and Partners. Challenging talk on #ResponsibleAI: Trust, Fairness, and Transparency in Machine Learning – and interesting panel with Leon Szeli and Fabian Mader. AI and ML…
MOOC: Industrial Artificial Intelligence at Siemens – from the impact of Deep Learning, the creation of Conversational AI, to AI-centric API ecosystem
Awesome – finishing the MOOC on Artificial Intelligence at Siemens – from the impact of Deep Learning, the creation of Conversational AIs, to the acceleration via an AI-centric API ecosystem. Proud to push the Siemens AI Lab further – accelerating…
End-to-End Trainable Attentive Decoder for Hierarchical Entity Classification
Abstract: We address fine-grained entity classification and propose a novel attention-based recurrent neural network (RNN) encoderdecoder that generates paths in the type hierarchy and can be trained end-to-end. We show that our model performs better on fine-grained entity classification than…
AI & Machine Learning with Meaningful Impact
My research connects the concepts and methods of social networks and the semantic web with machine learning and natural language processing. I am interested in combining human intelligence with artificial intelligence methodologies. I am specifically interested in methods that bridge the areas of connectionism and symbolic models applied to real-world applications
USI Answers: Natural Language Question Answering Over (Semi-) Structured Industry Data
Abstract: The paper reports on the progress towards the goal of offering easy access to enterprise data to a large number of business users, most of whom are not familiar with the specific syntax or semantics of the underlying data…
Market Intelligence: Linked Data-driven Entity Resolution for Customer and Competitor Analysis
Abstract: In this paper, we present a linked data-driven method for named entity recognition and disambiguation which is applied within an industry customer and competitor analysis application. The proposed algorithm primarily targets the domain of geoparsing and geocoding, but it…
Knowledge Enhanced Embodied Cognitive Interaction Technology (KnowCIT)
CITEC – Cognitive Interaction Technology – Center of Excellence Summary The project has built a technology which enables artificial agents to explore “crowdsourced” knowledge resources generated by large communities of web users. Project: Knowledge Enhanced Embodied Cognitive Interaction Technology Supervisor(s): Ipke…
German Polarity Clues
A Lexical Resource for German Sentiment Analysis: Feel free to use/download the GermanPolarityClues dictionary A new publicly available lexical resource for sentiment analysis for the German language The resource offers a number of 10.141 polarity features, associated to three numerical…
WikiQA – Question Answering
WikiQA is a German open domain question answering system that uses the Wikipedia as a knowledge base to answer natural language questions. It has been developed by the KnowCIT project (Artificial Intelligence Group) within the CITEC at Bielefeld University. Using…
