suzan @suzan@idf.social

Norbert Fuhr's recommendations for gaining scientific knowledge from experiments:

1. Do not use MRR or MAP;
2. Instead of relative improvements, regard the effect size!
3. For multiple significance tests, use a correction, such as Bonferoni or Tukey's HSD (NB comparing only to the 2nd best method does not help!)
4. There are no significant improvements for re-usable test collections! (hypotheses have to be formulated before the work)
#SIGIR2020

SIGIR 2020 highlights for people in European time zones:

Sunday 26 July
15:00-15:30h CEST -- Welcome & Opening
15:30-17:00h CEST -- Social Event (Student Event)

More at: https://sigir.org/sigir2020/

SIGIR 2020 highlights for people in European time zones:

Wednesday 29 July
8:30--9:30h CEST -- Keynote VI by Dacheng Tao: How Deep Learning Works for Information Retrieval
9:40-11:40h CEST -- Full paper session 8B, Multi-modal Retrieval and Ranking
13:00-14:00h CEST -- Playback Keynote V by Elizabeth Churchill: From Information to Assistance
15:00-18:00h CEST -- Business Meeting & Closing

SIGIR 2020 highlights for people in European time zones:

Tuesday 28 July
8:30--9:30h CEST -- Keynote IV by Norbert Fuhr: Proof by Experimentation? Towards Better IR Research
9:40-11:40h CEST -- Full paper session 5C, Information Access and Filtering
12:45-13:45h CEST -- Playback Keynote III by Ellen Voorhees: Coopetition in IR Research
14:00-16:00h CEST -- Posters/Demos/Social event
16:00-18:00h CEST -- Full paper session 6C Context-aware Modeling

SIGIR 2020 highlights for people in European time zones:

Monday 27 July
8:30--9:30h CEST -- Keynote II by Zong-Ben Xu: On Presuppositions of Machine Learning: A Meta Theory
9:40-12:00h CEST -- Full paper session 2B, User Behavior and Experience
13:00-14:30h CEST -- Women in IR Panel
14:45-15:45h CEST -- Playback Keynote I by Geoffrey Hinton: The Next Generation of Neural Networks
16:00-18:00h CEST -- Full paper session 3B, Learning to Rank

Periodic reminder of what #Google looks like now in one of the first #browser that was used to surf the web. Compared to the first website from CERN.

#Mozaic

Information Retrieval and Its Sister Disciplines. (arXiv:1912.02346v1 [cs.IR]) http://arxiv.org/abs/1912.02346

I ditched Google for DuckDuckGo. Here's why you should too:

https://www.wired.co.uk/article/duckduckgo-google-alternative-search-privacy

Beyond word embeddings: learning entity and concept representations from large scale knowledge bases http://link.springer.com/10.1007/s10791-018-9340-3

DIR 2019 program.

Unfortunately, the workshop is sold out (!).

http://www.dir2019.nl/program.html

#IR researcher in NL or B (or keen on visiting Amsterdam):

Better register soon: https://www.dir2019.nl may run out of capacity, so if you are not quick...

Universal Transformers: a transformer approach by Mostafa Dehghani and colleagues that also uses a recurrent feedback loop. Very interesting. #SIKS

https://arxiv.org/abs/1807.03819

Slides for all lectures at the #Siks #IR course:

https://www.informagus.nl/events/siks-ir-2019.html

Here, you also find the information for the group experiment of this afternoon.

Slides of @Claudia Hauff's SIKS course presentation "Machine Learning for #IR" available online!

https://docs.google.com/presentation/d/1Jiu5ZkRJVrrFmwtGJg9elClDah-f1eKXCEkQXORrchk/edit?usp=sharing

Full house for the #Siks #IR Course for PhD students in Utrecht, NL.

Faegheh Hasibi @fhasibi presenting the lecture on Entity Oriented Search now.

Morning program included Claudia Hauff on Learning to Rank and other Machine learning for #IR, and Hinda Haned on FAT* related topics such as algorithmic bias.

We're hiring a PhD Candidate for Transfer Learning for Federated Search!

https://www.ru.nl/english/working-at/vacature/details-vacature/?recid=1064653