… as an entity in the Google Knowledge Graph!

Which is funny, because “emerging entities” were the main topic of my PhD Thesis [1]. With my co-authors I’ve published research on:

1. Learning how to recognize “out-of-knowledge base” entities emerging on social media [2]
2. How our collective memory is formed through “emerging entities” on Wikipedia [3], and more generally
3. Entity retrieval and ranking [4] where Google’s so-called “Knowledge Panels” often served as examples…

(FYI: I’m not sure how I ended up there, the metadata seems to be coming from Google Scholar)

#vanitysearch

[1] D. Graus, “Entities of interest — discovery in digital traces,” PhD Thesis, 2017.
[Bibtex]

@phdthesis{graus2017entities,
title={Entities of Interest — Discovery in Digital Traces},
author={Graus, David},
year={2017},
month={6},
school={Informatics Institute, University of Amsterdam},
isbn={9789461828002},
url={https://hdl.handle.net/11245.1/51be80bb-1cbf-4633-8ff9-e3128e990bfa}
}

[2] D. Graus, M. Tsagkias, L. Buitinck, and M. de Rijke, “Generating pseudo-ground truth for predicting new concepts in social streams,” in Advances in information retrieval, Cham, 2014, p. 286–298.
[Bibtex]

@inproceedings{graus2014generating,
author={Graus, David and Tsagkias, Manos and Buitinck, Lars and de Rijke, Maarten},
title={Generating Pseudo-ground Truth for Predicting New Concepts in Social Streams},
booktitle={Advances in Information Retrieval},
year={2014},
publisher={Springer International Publishing},
address={Cham},
pages={286--298},
url={https://doi.org/10.1007/978-3-319-06028-6_24},
doi={10.1007/978-3-319-06028-6_24},
series = {ECIR '14}
}

[3] D. Graus, D. Odijk, and M. de Rijke, “The birth of collective memories: analyzing emerging entities in text streams,” Journal of the association for information science and technology, vol. 69, iss. 6, pp. 773-786, 2018.
[Bibtex]

@article{graus2018birth,
author = {Graus, David and Odijk, Daan and de Rijke, Maarten},
title = {The birth of collective memories: Analyzing emerging entities in text streams},
journal = {Journal of the Association for Information Science and Technology},
year = {2018},
volume = {69},
number = {6},
pages = {773-786},
doi = {10.1002/asi.24004},
url = {https://asistdl.onlinelibrary.wiley.com/doi/abs/10.1002/asi.24004},
eprint = {https://asistdl.onlinelibrary.wiley.com/doi/pdf/10.1002/asi.24004},
}

[4] D. Graus, M. Tsagkias, W. Weerkamp, E. Meij, and M. de Rijke, “Dynamic collective entity representations for entity ranking,” in Proceedings of the ninth acm international conference on web search and data mining, New York, NY, USA, 2016, p. 595–604.
[Bibtex]

@inproceedings{graus2016dynamic,
author = {Graus, David and Tsagkias, Manos and Weerkamp, Wouter and Meij, Edgar and de Rijke, Maarten},
title = {Dynamic Collective Entity Representations for Entity Ranking},
year = {2016},
isbn = {9781450337168},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/2835776.2835819},
doi = {10.1145/2835776.2835819},
booktitle = {Proceedings of the Ninth ACM International Conference on Web Search and Data Mining},
pages = {595–604},
numpages = {10},
keywords = {fielded retrieval, entity retrieval, entity ranking, content representation},
location = {San Francisco, California, USA},
series = {WSDM '16}
}

The paper we wrote with former FD team mates Feng Lu and Anca Dumitrache has been accepted for publication as a long paper at UMAP 2020, the 28th Conference on User Modeling, Adaptation and Personalization! (I fondly remember my last time at UMAP, in 2016 😏)

We have published a preprint of this paper, get it: here, or from arXiv.

• F. Lu, A. Dumitrache, and D. Graus, “Beyond optimizing for clicks: incorporating editorial values in news recommendation,” in Proceedings of the 28th acm conference on user modeling, adaptation and personalization, New York, NY, USA, 2020, p. 145–153.
  [Bibtex]

  @inproceedings{lu2020beyond,
  author = {Lu, Feng and Dumitrache, Anca and Graus, David},
  title = {Beyond Optimizing for Clicks: Incorporating Editorial Values in News Recommendation},
  year = {2020},
  isbn = {9781450368612},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/3340631.3394864},
  doi = {10.1145/3340631.3394864},
  booktitle = {Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization},
  pages = {145–153},
  numpages = {9},
  keywords = {usefulness, news recommendation, editorial values},
  location = {Genoa, Italy},
  series = {UMAP ’20}
  }

Update 08/05: Cool, @NickKivits mentioned our paper in his Villamedia column: “Het idee van de filterbubbel kan in de prullenbak“ and newsletter (with over 11k subscribers!)

I am particularly happy with this work because:

1️⃣ In our paper we show how you can align algorithm design across stakeholders (in this case: data scientists and journalists), by effectively modeling an editorial value (“dynamicness”) in the news recommender of Het Financieele Dagblad without losing accuracy.

2️⃣ We present (more) empirical proof that #recsys (can) offer(s) users *more* diverse, serendipitous, and dynamic lists of articles, compared to editorially curated lists, and hence (can) help in *avoiding*, not creating filter bubbles!

3️⃣ It is the perfect wrap-up of our Google DNI-funded “SMART Journalism” project at FD Mediagroep (we wrote most of the paper in our spare time after the project ended).

See below the video of the talk at UMAP 2020 below:

I was invited to join the program committee of (the first) PodRecs: Workshop on Podcast Recommendations (to be held at RecSys’20).

Since our work on BNR SMART Radio, I am really interested in the space of audio, recommender systems, and information retrieval. Curious to see the submissions!

See the PodRecs call for papers, and check out the website, by clicking the image below.

Oberon Berlage’s MSc. thesis: “Improving automated segmentation of radio shows with audio embeddings” which he wrote under my supervision during his internship at FD Mediagroep was awarded a 9/10, under condition that the work was publishable.

Turns out it was, as it was recently accepted at IEEE ICASSP2020 (the 45th International Conference on Acoustics, Speech, and Signal Processing) without any additional work/experiments (just a bit of reduction). But you already knew this… Oberon will be presenting this work in Barcelona, thanks to the generous support of UvA’s Information Studies program.

We now published a preprint, read it below:

• O. Berlage, K. Lux, and D. Graus, “Improving automated segmentation of radio shows with audio embeddings,” in Icassp 2020 – 2020 ieee international conference on acoustics, speech and signal processing (icassp), 2020, pp. 751-755.
  [Bibtex]

  @inproceedings{berlage2020improving,
  author={O. {Berlage} and K. {Lux} and D. {Graus}},
  booktitle={ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  title={Improving Automated Segmentation of Radio Shows with Audio Embeddings},
  year={2020},
  pages={751-755},
  doi={10.1109/ICASSP40776.2020.9054315},
  url={https://doi.org/10.1109/ICASSP40776.2020.9054315}
  }

His work revolved around improving BNR SMART Radio‘s text-based segmentation by incorporating audio signals in the form of audio embeddings. This turns out to improve over our text-based baseline by a whopping +32.3% F1-measure!

Even better: an audio-only approach, trained on a smallish openly available dataset, outperforms our text-only baseline by 9.4%. This means the segmentation method can be employed without need for audio transcription, which could be a money-saver.

I was invited by UvA’s Information, Communication and the Data Society (ICDS) to participate in a panel at the Conference on Privacy and Data Protection, which was focused on AI.

The recording of the panel is now online, watch me telling a room full of (highly) privacy-aware (and cookie-averse) people that Cambridge Analytica nudging people to “politically activate them” with tailored information can be a “democratic good” 😅.

See the recording below:

For more information, see CPDP’s page of the panel.

For the Media Perspectives (“platform for media & innovation”) newsletter I wrote a column on the future of media & AI: Algoritmewijsheid. Read it below (in Dutch):

Enjoyed giving a lecture at the SIKS Course “Advances in Information Retrieval” at the Mitland Hotel in Utrecht. I also pitched DIR 2019 😅 (as evidenced by the picture above from Arjen). See my slidedeck below!

This talk is loosely based on (part of) the talk I gave at the ACM RecSys Summerschool, but I added a few slides on dealing with implicit feedback (= clicks), and popularity bias.

With Daan Odijk I gave a lecture + hands-on workshop at the ACM Summer School on Recommender Systems in Gothenburg, Sweden on RecSys in the Media Industry: Relevance, Recency, Popularity, and Diversity.

For it, we had a long (90+ min) lecture combining insights, experiences, and projects from our work at RTL and Blendle (Daan), and FD Mediagroep (me).

In addition, we did a small hands-on workshop, implementing a content-based re-ranker for WikiNews.

See our slides and notebooks here: https://github.com/graus/recsys_summer_school/

See a tweet by @alansaid, here:

Day three of the @ACMRecSys summer school is on. @dodijk and @dvdgrs talking about #recsys in media. #recsys2019 pic.twitter.com/NRV1H7A0So

— Alan Said (@alansaid) September 11, 2019

Finally, see my slidedeck here:

Update (28/1/2020): Oberon’s thesis was accepted and will be published at the IEEE 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), to be held May 4-8 in Barcelona, Spain! The submission is co-authored with Klaus Lux and myself.

Oberon Berlage recently successfully defended his MSc. thesis (title above!) for the Data Science Master at University of Amsterdam, and graduated with a whopping 9!

He’s the first academic offspring of our AI Team @ FD Mediagroep, and worked on BNR SMART Radio‘s segmenter. Oberon improved our text-based segmenter by adding audio embeddings, improving the F1 score with +32%!

His thesis is now online, check it out at: http://scriptiesonline.uba.uva.nl/document/673254

Yesterday BNR SMART Radio won two Dutch Interactive Awards (DIA 2019) Awards! We were nominated together with Elastique, the folks who designed the UX/interface of our BNR SMART Radio app which you can download here (or in your app stores, both Android/iOS)!

🥇 Content

We won Gold in the category “Content”. Why, you may ask?

“Finally a reason to listen to Radio in general, and BNR in particular. Because advertising is absent and topics are tailored to the personal taste of the listener, who can search in a targeted way and express appreciation for a broadcast through a thumbsup, they reach new target audiences online.”

jury report (source: emerce)

🥈 Disruptor

Next to this, we also won the Silver DIA2019 Award in the category “Disruptor”!

“In a world where radio has never deviated from the linear model, the jury finds this very disruptive. SMART Radio provides a personal radio experience and possibly a new revenue model in the long term. The jury members find the potential of the underlying strategy even more impressive. What if BNR joins forces with FD Mediagroep and combines the work of both parties in this? The jury sees all kinds of opportunities to fit in new forms of advertising (or to omit them). The collaboration between the agency and the media company has resulted in something that has never been seen before.”

jury report (source: emerce)

Current standing

For who has trouble keeping track 😅, these are the awards we won with SMART Radio:

🏆 Marconi Online Award
🏆 AMMA Award (with SMART Journalism)
🏆 DIA2019 Award, category: Content
🥈 DIA2019 Award, category: Disruptor