Yesterday I gave a (tongue-in-cheek) talk on algorithmic personalization at the VOGIN-IP Lezing 2018, and brought five pieces of evidence to prove the “filter bubble” doesn’t exist. Check out my slides (in Dutch) by clicking on the picture below!

For Company.info I wrote a short blog post explaining the current state-of-the-art, our current, and future projects that involve machine learning and company information. Click the image below to read the post! (in Dutch)

Here are the slides of a talk I gave at the Data Science Northeast Netherlands Meetup, where I detail the custom in-house entity linking framework, sentiment analysis, and entity salience scoring model we developed for Company.info (part of FD Mediagroep), in addition to showing some example applications of our corpus of news articles linked to organization profiles.

I’m sharing it here because I think it’s cool, since it’s one of the first project I’ve done at Company.info! Gives you some idea of what we’re working on..

Thursday 19 October, I had the pleasure of hosting the 8th Recommender Systems Amsterdam meetup at FDMG/Company.info. The meetup’s theme was media-content recsys, and we had three talks from industry, dealing with recommending tv programs, music videos, and text articles);

1. Ghida Ibrahim (Senior Data Scientist, (formerly at) Liberty Global): “Recommender systems for video and TV products”
2. Bouke Huurnink and Roman Ivanov (XITE): “Music Video Recommendation@XITE”
3. Robbert van der Pluijm (Head of Bibblio Labs, Bibblio): “Scaling a recommendation service – a threefold story”

Company.info wrote a small blog post about it, check it out here: Meetup: het succes van algoritmen en systemen voor personalisatie en aanbevelingen

Voor de debatavond De Macht van Data gaf ik een korte inleiding over algoritmen. Wat is een algoritme? Hoe werkt een algoritme? En waar komen we algoritmen tegen?

And it was a beautiful day. Thanks to everyone who attended my defense, to Daan for this (+ more) great picture, my paranymphs Rutger and Marijn for nymphing like a boss, and my committee for grilling but not burning me. Band pic:

Me and the gang. Photo by Daan Odijk.

My PhD thesis, Entities of Interest — Discovery in Digital Traces is now available for download. Click on the cover below to head to graus.co/entities-of-interest and grab your electronic copy of the little booklet that took me 4+ years to write!

On Tuesday May 9th I will participate in a panel discussion on Data & Democracy, which will revolve around the impact of (big) data (mining), profiling, and political micro-targeting on politics and campaigning of the future. Data & Democracy is organized by the Personalised Communication group (a joint effort between UvA’s Communication Science & Information Law groups). See this article (in Dutch) and the flyer (below) for more information!

I was invited to give the opening keynote at the Intelligence Day of the Koninklijke Marechaussee (Military Police) on Big Data and Machine Learning, with the aim to explain the audience what ML and Big Data is.

I spent a disproportionate amount of time on Algorithmic Bias, because I think this is a hugely important topic — in particular for this audience! See the slides of my talk (in Dutch) below, or on slideshare:

Our paper,

• D. Graus, P. N. Bennett, R. W. White, and E. Horvitz, “Analyzing and predicting task reminders,” in The 24th conference on user modeling, adaptation and personalization, 2016.
  [Bibtex]

  @inproceedings{graus2016analyzing,
  title={Analyzing and Predicting Task Reminders},
  author={Graus, David and Bennett, Paul N and White, Ryen W and Horvitz, Eric},
  booktitle={The 24th Conference on User Modeling, Adaptation and Personalization},
  year={2016},
  organization={ACM}
  }

was awarded best student paper, at UMAP 2016!

Me receiving the award during the UMAP banquet dinner at the Marriott Harbourfront Hotel, Halifax. Photo by Denis Parra.