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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)

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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)

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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

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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

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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

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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

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

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Beyond word embeddings: learning entity and concept representations from large scale knowledge bases link.springer.com/10.1007/s107

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

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

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

arxiv.org/abs/1807.03819

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Slides for all lectures at the course:

informagus.nl/events/siks-ir-2

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

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Full house for the 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 , and Hinda Haned on FAT* related topics such as algorithmic bias.

"The merits of Universal Language Model Fine-tuning for Small Datasets - a case with Dutch book reviews"

arxiv.org/abs/1910.00896

Work by Benjamin van der Burgh @LIACS, evaluating the effectiveness of ULMFiT for small training sets

Data: arxiv.org/abs/1910.00896

Vacancies!

15 fully-funded PhD Positions on Domain-Specific Search (EU Marie Curie Action project)

ifs.tuwien.ac.at/dossier/phd_p

I am hiring for project 6 and 7, addressing transparency and explainability in legal search.

w/ @arjen @leifos

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Ik heb vandaag een bachelordiploma uitgereikt aan een student die geboren is in het jaar dat ik eindexamen deed.

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Mastodon

The "unofficial" Information Retrieval Mastodon Instance.

Goal: Make idf.social a viable and valuable social space for anyone working in Information Retrieval and related scientific research.

Everyone welcome but expect some level of geekiness on the instance and federated timelines.