The Information and Language Processing Systems group is part of the Informatics Institute of the University of Amsterdam. Our research is aimed at intelligent information access, especially in the face of massive amounts of information. We work on finding and analyzing content (information retrieval, machine translation, language technology), the analysis of structural information (social networks, linked data) and the analysis of user behavior (self-learning search, log analysis, user studies).

We combine fundamental, experimental and applied research, and we do so using a broad range of textual data, data from the web or enterprises, edited or user generated, or obtained from (automatic) transcriptions of audio or video. We are involved in a large number of projects with other groups, both within and outside academia. Our research is funded by NWO, KNAW, the EU and through a range of public-private partnerships.

Recent News

Catching ILPS-ers at SIGIR 2016

irtalk_400x400Several ILPS-ers will be at SIGIR 2016 next week. Come talk to us. We’re presenting a number of papers:

  • A Context-aware Time Model for Web Search. Alexey Borisov, Ilya Markov, Maarten de Rijke, Pavel Serdyukov
  • Balancing Relevance Criteria through Multi-Objective Optimization. Joost van Doorn, Daan Odijk, Diederik M. Roijers, Maarten de Rijke
  • Click-based Hot Fixes for Underperforming Torso Queries. Masrour Zoghi, Tomáš Tunys, Lihong Li, Damien Jose, Junyan Chen, Chun Ming Chin, Maarten de Rijke
  • Evaluating Retrieval over Sessions: The TREC Session Track 2011-2014. Ben Carterette, Paul Clough, Mark Hall, Evangelos Kanoulas, Mark Sanderson
  • Explainable User Clustering in Short Text Streams. Yukun Zhao, Shangsong Liang, Zhaochun Ren, Jun Ma, Emine Yilmaz, Maarten de Rijke
  • Is This Your Final Answer? Evaluating the Effect of Answers on Good Abandonment in Mobile Search. Kyle Williams, Julia Kiseleva, Aidan C. Crook, Imed Zitouni, Ahmed Hassan Awadallah, Madian Khabsa
  • Predicting User Satisfaction with Intelligent Assistants. Julia Kiseleva, Kyle Williams, Ahmed Hassan Awadallah, Aidan C. Crook, Imed Zitouni, Tasos Anastasakos
  • Seeking Serendipity: A Living Lab Approach to Understanding Creative Retrieval in Broadcast Media Production. Sabrina Sauer, Maarten de Rijke
  • Selectively Personalizing Query Auto-Completion. Fei Cai, Maarten de Rijke
  • Using Sparse Coding for Answer Summarization in Non-Factoid Community Question-Answering. Zhaochun Ren, Hongya Song, Piji Li, Shangsong Liang, Jun Ma, Maarten de Rijke

We also co-organize a workshop:

  • Workshop on Neural Information Retrieval (Neu-IR 2016), Nick Craswell, W. Bruce Croft, Maarten de Rijke, Jiafeng Guo, Bhaskar Mitra

a tutorial:

  • Online Learning to Rank for Information Retrieval, Artem Grotov, Maarten de Rijke

and contribute to the doctoral consortium:

  • Measuring Interestingness of Political Documents, Hosein Azarbonyad

Finally, former ILPS-ers are heavily involved with the Industry Track (SIRIP):

  • Industry Track (SIRIP), Jussi Karlgren, Gilad Mishne
  • Building a Self-Learning Search Engine: From Research to Business, Manos Tsagkias, Wouter Weerkamp

and with one of the other workshops:

  • Workshop on Search as Learning (SAL 2016), Jacek Gwizdka, Preben Hansen, Claudia Hauff, Jiyin He, Noriko Kando

Collaboration Blendle and ILPS

blendle-logoTo improve their services Blendle starts an exploratory cooperation with the UvA as academic partner. Together with ILPS-ers De Rijke and Sijaranamual they will work on optimizing Blendle’s search and recommendation facilities. In particular, the collaboration will use state-of-the-art methods for mining knowledge graphs and for online evaluation to improve the findability of Blendle’s articles.