We're hiring (Frederik Zuiderveen Borgesius and me)!
A PhD Candidate for Fairness and Non-discrimination in Machine Learning for Information Retrieval and Recommendation


Nice, a new dataset by @mohammad to evaluate open-domain single- and multi-turn conversations and clarification questions:


“A Joint Two-Phase Time-Sensitive Regularized Collaborative Ranking Model for Point of Interest Recommendation” accepted for publication on #IEEE Transactions on Knowledge and Data Engineering #TKDE w/ Dimitrios Rafailidis and Fabio Crestani

"In Situ and Context-Aware Target Apps Selection for Unified Mobile Search" to appear at #CIKM2018; with Zamanii, Crestani, and Croft.

Preprint: bit.ly/2Nzi1Sz

ISTAS data collection: bit.ly/ISTASpage

uSearch Android app code: bit.ly/uSearchOnGitHub

Our paper "In Situ and Context-Aware Target Apps Selection for Unified Mobile Search" with Zamani, Crestani, and Croft accepted as a full paper to #CIKM2018

Our full paper "A Collaborative Ranking Model with Multiple Location-based Similarities for Venue Suggestion" w/ Dimitrios Rafailidis and Fabio Crestani accepted at #ICTIR2018

Our paper on personalized context-aware point of interest recommendation has been accepted at ACM TOIS; pre-print available here: bit.ly/2LS7P7n

"Target Apps Selection: Towards a Unified Search Framework for Mobile Devices" to appear at #sigir2018.
Preprint: goo.gl/BVmR9Y
Data: goo.gl/WCKRzd

We are also looking for a PhD candidate, on a fully funded position:

The PhD candidate will study information retrieval over large and evolving graphs. How can we combine structured queries formulated in a graph query language with ’keyword’ queries, and express ranking functions that take into account the graph structure? What query processing techniques can enable scalable and efficient retrieval systems over evolving graphs?

More information:

Switching to voice commands...so much pain in both hands 😞

Here I am. Hi again. So glad to gave an IR home 😍


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.