The Papers “Anytime Bottom-Up Rule Learning for Knowledge Graph Completion” by Christian Meilicke, Melisachew Wudage Chekol, Daniel Ruffinelli and Heiner Stuckenschmidt and “PRoFET: Predicting the Risk of Firms from Event Transcripts” by Christoph Kilian Theil, Samuel Broscheit and Heiner ...

The article „Using the Semantic Web as a Source of Training Data“ by Christian Bizer, Anna Primpeli, Ralph Peeters has been accpeted for the upcoming special issue on “Data and Repeatability” of Datenbank Spektrum.

The Paper “newNECTAR: Collaborative active learning for knowledge-based probabilistic activity recognition” by Gabriele Civitarese, ClaudioBettini, TimoSztyler, DanieleRiboni, and HeinerStuckenschmidt has been accpeted for Pervasive and Mobile Computing (Impact Factor 2.974)

The joint paper with the Chair of Logistics and Supply Chain Management “A Data-Driven Newsvendor Problem: From Data to Decision” by Jakob Huber, Sebastian Müller, Moritz Fleischmann and Heiner Stuckenschmidt has been accepted for the European Journal on Operational Research (Impact Factor 3.428).

The paper “Real-Time Smart Charging Based on Precomputed Schedules” by Oliver Frendo, Nadine Gärtner and Heiner Stuckenschmidt has been accepted by IEEE Transactions on Smart Grid (Impact Factor 7.364)

The paper “HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings” by Saba Anwar, Dmitry Ustalov, Nikolay Arefyev, Chris Biemann, Simone Paolo Ponzetto, and Alexander Panchenko has been accepted for publication at SemEval 2019. Abstract: We present our ...

The article “Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction” by Dmitry Ustalov, Alexander Panchenko, Chris Biemann, and Simone Paolo Ponzetto has been accepted for publication at the Computational Linguistics (CL) journal by MIT Press. Abstract: We present a ...

The article „A Unified Framework for Frequent Sequence Mining with Subsequence Constraints“ by Kaustubh Beedkar, Rainer Gemulla und Wim Martens has been accepted for publication in ACM Transactions on Database Systems (TODS). Abstract: Frequent sequence mining methods often make use of constraints ...

Prof. Graeme Hirst from the University of Toronto is visiting the DWS Group during March. Graeme is well known for his work on natural language processing. He will work with PhD students from the AI and the NLP Area on advanced methods for argumentation analysis in natural language texts. For more ...

The paper „Scalable Frequent Sequence Mining With Flexible Subsequence Constraints“ by Alexander Renz-Wieland, Matthias Bertsch, and Rainer Gemulla has been accepted at the 2019 IEEE International Conference on Data Engineering (ICDE). Abstract: We study scalable algorithms for frequent sequence ...