Advancing intelligent access to information.
AIRA is a research group focused on intelligent systems for information retrieval and access. Our work covers the design and evaluation of search and recommendation methods, data acquisition and processing, the use of machine learning models for natural language understanding and generation, social network analysis, and the development of explainable and agent-based artificial intelligence systems.
A decade of research impact
Between 2015 and 2025, AIRA has consolidated an active international research profile with significant scientific production, competitive projects, and doctoral training in information retrieval, recommendation systems, natural language processing, and explainable AI.
76
JCR journal articles
101
International conferences
23
Research projects
16
Technology transfer projects
12
PhD dissertations
Research Areas
AIRA develops advanced methods and intelligent systems for information access, recommendation, language technologies, social data analysis, and explainable AI.
Information Retrieval
Design and evaluation of intelligent retrieval systems, semantic search, ranking methods, and interactive access to large-scale information collections.
Recommender Systems
Personalized recommendation models for multimedia, educational, and online platforms using collaborative, content-based, and hybrid approaches.
Natural Language Processing
Machine learning and large language model techniques for text understanding, generation, conversational systems, and multilingual applications.
Social Network Analysis
Analysis of online communities, information diffusion, user behavior, and interaction patterns in digital social environments.
Explainable and Agent-Based AI
Transparent and interpretable AI systems, autonomous agents, and trustworthy machine learning for decision support and human-AI interaction.
Research Team
AIRA brings together researchers and collaborators in information retrieval, recommender systems, natural language processing, and explainable artificial intelligence.
Professors
Alejandro Bellogín Kouki
Iván Cantador Gutiérrez
Fernando Díez Rubio
Lara Quijano Sánchez
José Luis Jorro Aragoneses
Ilia Stepin
External Researchers
Pablo Sánchez Pérez
Federico Liberatore
Pablo Mateos Masa
Recent Publications
Selected publications from conferences and journals in information retrieval, machine learning, and human-centered AI.
Analysing the Effect of Recommendation Algorithms on the Spread of Misinformation
Recommendation fairness in e-participation: Listening to minority, vulnerable and NIMBY citizens
A Conversational Agent for Argument-driven E-participation
Point of Interest Recommendation: Pitfalls and Research Directions
The role of recommendation algorithms in the formation of disinformation networks
Impacts of Mainstream-Driven Algorithms on Recommendations for Children Across Domains: A Reproducibility Study
Smart imputation, better recommendations: Improving traditional point-of-interest recommendation through data augmentation
Improving Novelty and Diversity of Nearest-Neighbors Recommendation by Exploiting Dissimilarities
Context Trails: A Dataset to Study Contextual and Route Recommendation
Modeling disinformation networks on Twitter: structure, behavior, and impact
Quantifying polarization in online political discourse
Hate speech on Twitter: Profiling users and interaction analysis in the Spanish language
AGORA: An intelligent system for the anonymization, information extraction and automatic mapping of sensitive documents
Towards social fairness in smart policing: Leveraging territorial, racial, and workload fairness in the police districting problem
A software solution for building fuzzy-grounded interactive dialogue-based explanations
Information-seeking dialogue for explainable artificial intelligence: Modelling and analytics
A proof of concept on dialogue games for explainable artificial intelligence
An empirical study on how humans appreciate automated counterfactual explanations which embrace imprecise information
Collaborate with AIRA
We are open to academic collaborations, industrial partnerships, and student applications in AI and Information Retrieval.