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I am happy to share that our paper on the « for Large-Scale Geometric Learning» was published today at (openreview.net/pdf?id=85BfDdYM)

What an honor to start the year 2023 with our meeting on the combination of concept lattices and topological data analysis: dagstuhl.de/de/seminars/semina

What comes next? Apart from adding more research fields, we will add topic models and integrate the possibility to search for topic flows, i.e., you can select particular authors and find out who they influenced on what topic.

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With this , you can analyze the flow within computer science or . More research areas are to come in the next weeks, e.g., , , , etc. You can have an overview over a whole area or select interesting or .

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It is based on our recently published applied work, appeared in : doi.org/10.1007/s11192-022-045

We derive a topic based from a co-authorship graph by attributing to authors, based on the topics of their research work.

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A new tool based on our work on measuring in co-authorship was released yesterday to the public: flowtest.sci-rec.org/

It is still and and a bit , so please be ;)

Formal Context

This server is meant to be a haven for people who research and apply both computer science as well as mathematics, in particular algebra, and their fans ;)