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@ISG-Siegen

Intelligent Systems Group, University of Siegen

Welcome to the code repository of the Intelligent Systems Group (ISG), headed by Prof. Joeran Beel. We conduct research in recommender-systems (RecSys), personalization and information retrieval (IR) as well as on automated machine learning (AutoML), meta-learning and algorithm selection. Domains we are particularly interested in include smart places, eHealth, manufacturing (industry 4.0), mobility, visual computing, and digital libraries.

We founded and maintain, among others, Darwin & Goliath, Recommender-Systems.com, Mr. DLib, and Docear, each with thousand of users; we contributed to TensorFlow, JabRef and others; and we developed the first prototypes of automated recommender systems (AutoSurprise and Auto-CaseRec) and Federated Meta Learning (FMLearn Server and Client).

Our homepage: https://isg.beel.org/

Our code: https://code.isg.beel.org/

Twitter 1: https://twitter.com/JoeranBeel

Twitter 2: https://twitter.com/RecSys_c

Popular repositories

  1. Auto-Surprise Auto-Surprise Public

    An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀

    Python 26 2

  2. assembled assembled Public

    A framework to find better ensembles for (Automated) Machine Learning

    Python 5 3

  3. Algorithm-Performance-Personas Algorithm-Performance-Personas Public

    Python 1 2

  4. lenskit-auto lenskit-auto Public

    An AutoRecSys Library built around LensKit. Performs automatic algorithm selection, hyperparameter optimzation and ensembling on LensKit models.

    Python 1 1

  5. camels camels Public

    Python 1

  6. scoring-optimizer scoring-optimizer Public

    Python 1

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