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.
Two more talks are coming up, mark your agenda’s. The usual recipe: one industry speaker, one academic speaker and drinks afterwards. Bouke Huurnink (Sound and Vision) will talk about “Integrating Automatic Annotations in Audiovisual Search”. Ivan Titov (ILLC) will talk about “Learning Shallow Semantics with Little or No Supervision”
Daan Odijk (ILPS) received the CIKM’15 Best Student Paper Award for his paper “Struggling and Success in Web Search”. This full paper is the result of his internship at Microsoft Research in Redmond. In this joint work with Daan Odijk, Ryen White, Ahmed Hassan Awadallah and Susan Dumais, they investigate why some web searchers succeed where others struggle.
Friday October 16, 16:00-17:00
Speaker: Emine Yilmaz (University College London, Microsoft Research Cambridge)
Title: Task-based Information Retrieval
Wu Chuan has joined ILPS as a PhD student funded by China Scholarship Council. He will be working on entity based information retrieval under the supervision of Evangelos Kanoulas and Maarten de Rijke.
Evangelos Kanoulas has been awarded a Google Faculty Research Award for his proposal ‘Session-based Personalization: Analysis and Evaluation’, to conduct research on personalizing search engine results on the basis of user interactions with the search engine on the current session.
The Google Research Awards Program received 805 strong proposals and funded 113 of them, with only 3 of them in the fields of Information retrieval, extraction and organization (including semantic graphs).
Adith Swaminathan and Tobias Schnabel are visiting for one year. They are both PhD students at Cornell University working in the intersection of machine learning and information access. Adith’s main focus is on batch learning from bandit feedback using counterfactual risk estimators, developing the learning algorithms and the underlying theory for principled learning from logged interaction data. Tobias works on principled methods for evaluation, including the evaluation of embedding methods for text and the use of propensity scoring for reducing bias in recommender-system evaluation due to self-selection effects.