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.
moreNews - Data Science Chair
Our paper "CoBERT: Scientific Collaboration Prediction via Sequential Recommendation" has been accepted at the Second International Workshop on Neural Recommender Systems @ ICDM-21.
moreOur paper “Learning Mathematical Relations Using Deep Tree Models” has been accepted at IEEE ICMLA 2021 special session “Machine Learning for Graphs”.
moreOur workshop paper "Detecting Presence Of Speech In Acoustic Data Obtained From Beehives" got accepted at the DCASE21 (Workshop on Detection and Classification of Acoustic Scenes and Events) and will be presented in November this year
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We analyze the learned features of models trained with different deep metric learning loss functions on two scales (pixel and image property level) and find that ranking and classification based loss functions tend to differ significantly.
moreThe paper "Comparison of Transformer-Based Sequential Product Recommendation Models for the Coveo Data Challenge" is our contribution to the Coveo Data Challenge organized by the e'Com Workshop at the SIGIR 21.
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Our case study on sampling strategies for evaluating neural sequential item recommendation models has been accepted for publication at RecSys 2021.
moreOur paper "Semi-unsupervised Learning: An In-depth Parameter Analysis" got accepted for publication at "KI2021".
moreDas Staatliche Bauamt Würzburg hat einen Kurzfilm gedreht, der den aktuellen Stand auf der ZPD Baustelle dokumentiert und interessante Informationen zu den wissenschaftlichen Inhalten und zur architektonischen Umsetzung dieses spannenden Forschungsbaus der JMU vermittelt.
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The article will be published in Springer's Machine Learning journal in the ECMLPKDD 2021 special issue.
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