This site describes the activites of the MRIM research group.

The MRIM group studies methods for satisfying user information needs. These needs have largely evolved over time, as well as contexts in which they are formulated and the methods by which they are satisfied.
The context of Information Retrieval (IR) has broadened not only to include all types of data (texts, images, video, etc.), but also to include all types of users, and IR has been widely used through other applications (filtering, recommending systems, social networks, etc.). More recently, concerns about the fairness and the transparency of IR systems has emerged and the recent GDPR European Union regulation has introduced a “right to explanation” on algorithmic decision-making, which all IR systems or methods are subject to. This is especially challenging, as most of them now involve “deep learning black boxes”.
As in many other domains, learning-based methods, with, as a corollary, the use and building of large annotated collections, have become dominant for almost all aspects of IR. Such point should not however be considered as exclusive, as other fundamental aspects of information retrieval (like new extensions of existing models of IR) are still under concern in this research field.

MRIM has conducted research on the following themes:

• Modeling of IR systems
• Semantic indexing
• Multimedia Indexing
• Transparency and explainability
• Social Networks and Personalization
• IR in Under-Resourced Languages
• Mobile and Cultural Heritage
• Medical IR
• IR for E-tourism
• IR and Smart Cities
• Evaluation of IR systems

All our research work is described here.

Our 2019 activity report is available here.

Laboratoire d'Informatique de Grenoble
Bâtiment IMAG
700 avenue Centrale
CS 40700, 38058 Grenoble Cedex 9 - France
Phone: +33 4 57 42 15 48
Group Leader: Georges QUÉNOT

Paper accepted for EDBT 2020 "Fairness in Online Jobs: A Case Study on TaskRabbit and Google", with S. Amer-Yahia, S. Elbassuoni, A. Ghizzawi, R. M. Borromeo , E. Hoareau and P. Mulhem.

Anuvabh Dutt defended brilliantly his PhD thesis on December 17th 2019 :

Le 2 décembre 2019, un article publié sur le blog BInaire sur le testing algorithmique.

Kodicare (continuous evaluation of web search engines) ANR International Research Project acccepted for funding. Cooperation with RSA Vienna and Qwant. 3 years, from 11/2019.

The paper "Quelques pas vers l'Honnêteté et l'Explicabilité de moteurs de recherche sur le Web." Philippe Mulhem, Lydie du Bousquet, Sara Lakah, was awarded Best paper of the CORIA 2019 conference,

We organized the 40th European Conference in Information Retrieval (ECIR) in march 2018