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Data Science Chair

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About Us

The Data Science Chair (formerly DMIR Research Group) is a highly interdisciplinary group of researchers led by Prof. Andreas Hotho. We are active in machine learning research with applications in multiple domains, namely environmental sensing, natural language processing, recommendation, semantic web and fraud detection.

News

Wir trauern um Daniel Zoller

Viel zu früh verstarb unser Freund und Kollege Daniel Zoller am 05.10.21 nach schwerer Krankheit.

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Symposium zu „Mensch - Recht - Digitalisierung“

Auf dem gemeinsamen Symposium zum Thema "Mensch - Recht - Digitalisierung" des Oberlandesgericht Bamberg und der Julius-Maximilians-Universität Würzburg in der Neubaukirche hielt heute auch Prof. Dr. Andreas Hotho einen Vortrag mit dem Thema "Künstliche Intelligenz im (Un-)Recht?"

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Our paper "Sequential Item Recommendation in the MOBA Game Dota 2" has been accepted at NeuRec@ICDM 2021

In our paper, we introduce a large dataset of in-game item purchase logs from the MOBA game Dota 2 and evaluate the performance of state-of-the-art sequential item recommendation algorithms for helping users to correctly itemize during a game.

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Our paper "CoBERT: Scientific Collaboration Prediction via Sequential Recommendation" has been accepted at NeuRec@ICDM 2021

Our paper "CoBERT: Scientific Collaboration Prediction via Sequential Recommendation" has been accepted at the Second International Workshop on Neural Recommender Systems @ ICDM-21.

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Lectures

Our lectures and seminars cover fundamental topics like databases and algorithms as well as more specific methods like natural language processing, machine learning, information retrieval.

An overview can be found here.

Theses and Practica

We offer various topics for theses and practica on all our research topics. As a BA/MA student you will have access to the CAIDAS cluster to do your research.

Find your thesis topic here!

Job Offerings

We're always looking for help, whether with research related topics, teaching or administration and offer work for variable amounts of hours. You'll also gain access to the CAIDAS cluster for your work.

For more information, check out our job offers!