The IKR3 laboratory is involved in numerous projects that address issues related to Information Retrieval, Natural Language Processing, Artificial Intelligence, and Social Computing.
LeMuR: Learning with Multiple Representations
LeMuR is an MSCA (Marie Skłodowska-Curie Actions) Doctoral Network (DN) 2021 on Learning with Multiple Representations. The goal of LeMuR is to develop the theoretical foundations and a first set of algorithms for the new “Learning with Multiple Representations” (LMR) paradigm. Moreover, corresponding applications will be developed to demonstrate the usefulness of the new family of approaches. Specifically, LMR algorithms will allow flexible representations (e.g., suitable for explainability, fairness, …) with diverse target functions (e.g., incorporating environmental or even social impact) so as to make the induced models abide by the Green Charter and trustworthy AI criteria by design. The project will focus on learning with weak supervision because it addresses one of the major flaws of modern ML approaches, i.e., their data hunger, by means of weaker sources of labeling for training data. The outcome of the DN will be a set of 10 experts trained to implement the third and subsequent waves of AI in Europe. The highly interdisciplinary and intersectoral context in which they will be trained will provide them with research-related and transferable competencies relevant to successful careers in central AI areas.
DoSSIER: Domain-Specific Systems for Information Extraction and Retrieval
DoSSIER is an EU Horizon 2020 ITN/ETN on Domain-Specific Systems for Information Extraction and Retrieval. DoSSIER will elucidate, model, and address the different information needs of professional users. It mobilizes an excellent and highly synergistic team of world-leading Information Retrieval (IR) experts from 5 EU States who, together with 3 academic partners (universities in the US, Japan, and Australia), and 11 industrial partners (dynamic SMEs and large corporations) will produce fundamental insights into how users comprehend, formulate, and access information in professional environments.
The PerLIR project: Personal Linguistic resources in Information Retrieval
The PerLIR project is funded by the Italian Ministry of Research under the PRIN 2019 call with two research units involved: the University of Milano-Bicocca (Prof. Gabriella Pasi) and the Sapienza University of Rome (Prof. Roberto Navigli, head of the Linguistic Computing Laboratory (http://lcl.uniroma1.it, Department of Computer Science).
The aim of the project is to provide groundbreaking techniques able to bridge the gap between Information Retrieval and multilingual Natural Language Processing to innovate:
- The way a user model is created, thanks to the automatic creation of language-independent personal linguistic resources.
- The exploitation of personal linguistic resources in Information Retrieval to show the benefit of a language-independent, scalable user representation (which is at the same time customized to both the user preferences and her language usage) in retrieving the most relevant results to that user’s queries.