[isabelle] Update on the SErAPIS search engine: New videos

We would like to thank all of you who have so far given us feedback on your search results using the SErAPIS search engine for the Isabelle Libraries and AFP (https://behemoth.cl.cam.ac.uk/search/).

To help new users with trying out SErAPIS, we have now prepared two short introductory videos: Video 1 is a description of the search controls and Video 2 shows examples of searches and explains how you can give us feedback on the relevance of your search results via the SErAPIS interface.

You can now find them on the new YouTube channel:


(For more details, we remind that the user guide is also available here:

We hope that you can find the new videos useful and we would
really appreciate it if you could keep giving us your
feedback on your relevance judgements for the results of your searches
(as explained in Video 2) via the SErAPIS interface.

All data collected is anonymised.

Thank you!

Yiannos Stathopoulos and Angeliki Koutsoukou-Argyraki

On 2021-04-19 14:28, Dr A. Koutsoukou-Argyraki wrote:
PS. We would like to highlight that there are 6 different methods
available for you to try out.

Many thanks again for your valuable feedback.

With kind regards,

Yiannos and Angeliki

On 2021-04-19 12:13, Dr A. Koutsoukou-Argyraki wrote:
The ALEXANDRIA project is excited to announce the release of the
SErAPIS concept-oriented search engine for the Isabelle libraries and
AFP 2021.

Homepage: https://behemoth.cl.cam.ac.uk/search/
User Guide: https://behemoth.cl.cam.ac.uk/search/SErAPIS_online_user_guide.pdf

SErAPIS (Search Engine by the ALEXANDRIA Project for ISabelle) is an
experimental search engine for Isabelle designed to allow Isabelle
users to search and explore the libraries and AFP using
keywords and mathematical concepts (natural language phrases that
refer to mathematical objects and ideas).

We invite you to try it out. For tips on how to construct effective
queries, please see Section 3 of the user guide.

SErAPIS is also a platform for conducting research in novel methods to
search Isabelle collections and machine learning in Isabelle.

We kindly ask that you help us with our research by providing us with
feedback on the relevance of SErAPIS search results to your searches.
Giving us feedback is optional but very easy to do (see Section 4 of
the user guide).

Your feedback will help us:

(i)   build data-sets for Isabelle search and machine learning,
(ii)  develop new search algorithms for Isabelle collections and;
(iii) develop machine learning methods for aiding the construction of
proofs in Isabelle.

All data collected is anonymised.

Thank you,

Yiannos Stathopoulos and Angeliki Koutsoukou-Argyraki.

This archive was generated by a fusion of Pipermail (Mailman edition) and MHonArc.