I created another logo!
It is the textpipe logo, for textpipe;
a Python package for converting raw text in to clean, readable text and extracting metadata from that text.
textpipe’s readme
A package we’re developing together with our friends at De Persgroep and RTL Nederland :-).
In the latest AI Podcast, I am featured, talking with Li’ao Wang on our SMART Radio and SMART Journalism projects. Stream the episode below!
“Media is smart, but needs to get smarter. That’s what we’re working on here at the FD Mediagroep. Come and see what we do with AI to make our creators and content better.”
We’re demo’ing SMART Radio at The 17th Dutch-Belgian Information Retrieval workshop (DIR 2018). We wrote a short paper titled “SMART Radio: Personalized News Radio” to accompany the demo, read it by clicking below!
![[PDF]](https://i1.wp.com/graus.nu/blog/wp-content/plugins/papercite/img/pdf.png?ssl=1)
M. Sappelli, D. M. Chu, B. Cambel, J. Nortier, and D. Graus, “Smart radio: personalized news radio,” in The 17th dutch-belgian information retrieval workshop, 2018. @inproceedings{sappelli2018smartradio,
title={SMART Radio: Personalized News Radio},
author={Sappelli, Maya and Chu, Dung Manh and Cambel, Bahadir and Nortier, Joeri and Graus, David},
booktitle={The 17th Dutch-Belgian Information Retrieval workshop},
year={2018}
}
Our position paper ““Let Me Tell You Who You are” — Explaining Recommender Systems by Opening Black Box User Profiles” was accepted at the 2nd FATREC Workshop on Responsible Recommendation, held at RecSys ’18!
In this paper, we detail some our ideas and approaches of providing transparency in recommendations through displaying the user profiles, used ‘internally’ by our recommender system. Read the pre-print below!
D. Graus, M. Sappelli, and D. M. Chu, ““let me tell you who you are” — explaining recommender systems by opening black box user profiles,” in The 2nd fatrec workshop on responsible recommendation, 2018. @inproceedings{graus2018let,
title={“Let Me Tell You Who You are” — Explaining Recommender Systems by Opening Black Box User Profiles},
author={Graus, David and Sappelli, Maya and Chu, Dung Manh},
booktitle={The 2nd FATREC Workshop on Responsible Recommendation},
year={2018}
}
In the magazine IP (“journal for information professionals”) I am interviewed as one of three young professionals who show that ‘traditional categories and conceptual frames need to be readjusted.’
More specifically, it describes how my multi-disciplinary background, with an academic background in media studies, professional experience in the media, with a PhD in computer science, is important in bridging the gap between ‘techies’ and ‘non-techies’, and of particular value in my current role where I work on enabling AI in media.
In the context of a high-profile legal case (involving a bunch of data acquired from encrypted “Ennetcom” phones) I assisted lawyer Inez Weski in acquiring insights and trying to understand how digital forensic tools were used in the collection of digital evidence. I did this work in the context of my PhD research on semantic search for E-Discovery. In this post, I list some of the publications that followed from my work and the case.
Hansken is the search engine developed by the Netherlands Forensic Institute, and used by the police and public prosecutors. In this article in De Volkskrant, titled “Met deze eigen zoekmachine spit de politie schatten aan digitaal bewijs door,” I answered a few questions and explained my view on the role of Hansken in the court of law and digital evidence acquisition.
For more information on the case and my work, there’s a more in-depth piece on my work for Weski in the following NEMO Kennislink article, which details my findings and concerns with respect to using a proprietary, continuously developed, and largely black-box tool for collecting digital forensic evidence:
Finally, if you still didn’t have enough, there’s a blog post on crimesite which explains a bit more on the (legal) case, and some interpretations on my report and findings;
In RTL XL’s “How it’s done” me and Company.info’s CTO Henk Pijper explain why and how we apply AI and data science at Company.info to gain insights from online news.
Article on ‘robo-journalism’ in NRC Handelsblad, titled “Waar blijft de Nederlandse robotjournalist?” where I briefly mention our SMART Journalism project.
Our position paper “SMART Journalism: Personalizing, Summarizing, and Recommending Financial Economic News” was accepted at Algorithmic Personalization and News (APEN18) workshop, held at ICWSM ’18!
In this paper, we detail some of the ideas and opportunities of personalization in the domain of financial economic news. Read the pre-print below!
M. Sappelli, D. M. Chu, B. Cambel, D. Graus, and P. Bressers, “Smart journalism: personalizing, summarizing, and recommending financial economic news,” in The algorithmic personalization and news (apen18) workshop at icwsm ’18, 2018. @inproceedings{sappelli2018smart,
title={SMART Journalism: Personalizing, Summarizing, and Recommending Financial Economic News},
author={Sappelli, Maya and Chu, Dung Manh and Cambel, Bahadir and Graus, David and Bressers, Philippe},
booktitle={The Algorithmic Personalization and News (APEN18) Workshop at ICWSM '18},
year={2018}
}
Stimuleringsfonds voor de Journalistiek published an article on ‘robo-journalism’, where I say something about the SMART Journalism project we are doing at FDMG, which involves personalization and summarization of newspaper articles. Read it here! (pdf). Snippet:
Door introteksten te personaliseren, kun je meer doelgroepen bedienen.’ Bij het genereren van gepersonaliseerde intro’s op basis van artikelen, komt behoorlijk wat techniek kijken, vertelt David Graus, lead data scientist van het project bij het FD. ‘In de robotjournalistiek wordt nu vooral gewerkt aan het omzetten van gestructureerde data naar teksten. Wat wij willen is teksten maken op basis van door mensen geschreven teksten. Dat is behoorlijk cutting edge. We hebben daarom ook nauwelijks voorbeelden waar we ons op kunnen baseren.’
