12th Italian Information Retrieval Workshop 2022

Informal proceedings of the 12th Italian Information Retrieval Workshop 2022 Milan, Italy, June 29-30, 2022. Official proceedings are published online by CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073)

Edited by: Gabriella Pasi (1)
Paolo Cremonesi (2)
Salvatore Orlando (3)
Markus Zanker (4) (5)
David Massimo (4)
Gloria Turati (2)

(1) Università di Milano-Bicocca, Dipartimento di Informatica, Sistemistica e Comunicazione, Milano, Italy
(2) Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Milano Italy, Italy
(3) Università Ca’ Foscari Venezia, Dipartimento di Scienze Ambientali, Informatica e Statistica , Venezia, Italy
(4) Free University of Bozen-Bolzano, Faculty of Computer Science, Bolzano, Italy
(5) University of Klagenfurt, Institute of Artificial Intelligence and Cybersecurity, Klagenfurt, Austria

Table of Contents

Preface

Invited Talks:

• Pseudo-Relevance Feedback in the Era of Dense Retrieval
  Nicola Tonellotto

• From Implicit Data to Cognitive Models for Recommender Systems
  Marko Tkalcic

Accepted Papers:

• A Modular Approach to Topic Modeling for Heterogeneous Documents
  Giovanni Toto, Emanuele Di Buccio

• Addressing Privacy in Recommender Systems with Federated Learning
  Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Alberto Carlo Maria Mancino

• AI-based Decision Support Systems for the Management of E-rocurement Procedures
  Pasquale Lops, Marco Di Ciano, Nicola Lopane, Lucia Siciliani, Vincenzo Taccardi, Eleonora Ghizzota, Giovanni Semeraro

• An Analysis of Local Explanation with LIME-RS
  Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Francesco Maria Donini, Vincenzo Paparella, Claudio Pomo

• An Analysis of User Click Behaviour in Online Hotel Search
  Emanuele Cavenaghi, Lorenzo Camaione, Paolo Minasi, Gabriele Sottocornola, Fabio Stella, Markus Zanker

• Assessing the Semantic Difficulty of Queries
  Guglielmo Faggioli, Stefano Marchesin

• Choice Models for Simulating the Consumption of Recommendations
  Naieme Hazrati, Francesco Ricci

• Comparing ANOVA Approaches to Detect Significantly Different IR Systems
  Guglielmo Faggioli, Nicola Ferro

• Evaluating Recommendations in a User Interface With Multiple Carousels
  Maurizio Ferrari Dacrema, Nicolò Felicioni, Paolo Cremonesi

• Feature Selection via Quantum Annealers for Ranking and Classification Tasks
  Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini, Nicola Ferro, Guglielmo Faggioli, Paolo Cremonesi

• Group Dynamic and Group Recommender Systems for Decision Support
  Hanif Emamgholizadeh, Francesco Ricci

• Learning to Rank from Relevance Judgments Distributions
  Alberto Purpura, Gianmaria Silvello, Gian Antonio Susto

• Inverse Reinforcement Learning and Point of Interest Recommendations
  David Massimo, Francesco Ricci

• Recency, Popularity, and Diversity of Explanations in Knowledge-based Recommendation
  Giacomo Balloccu, Ludovico Boratto, Gianni Fenu, Mirko Marras

• Replication of Collaborative Filtering Generative Adversarial Networks on Recommender Systems
  Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Paolo Cremonesi

• Replication of Recommender Systems with Impressions
  Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Paolo Cremonesi

• Revisiting Retrieval-based Approaches for Conversational Recommender Systems
  Ahtsham Manzoor, Dietmar Jannach

• Sustainability driven Recommender Systems
  Pavel Merinov, David Massimo, Francesco Ricci

• Towards an Information Retrieval Evaluation Library
  Elias Bassani

Extended Abstracts:

• A Comprehensive Dataset for Modern Learning to Rank Solutions (Abstract)
  Domenico Dato, Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto

• Energy-Efficient Ranking on FPGAs through Ensemble Model Compression (Abstract)
  Veronica Gil-Costa, Fernando Loor, Romina Molina, Franco Maria Nardini, Raffaele Perego, Salvatore Trani

• Interpretable Ranking Using LambdaMART (Abstract)
  Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Alberto Veneri

• SOUR an Outliers Detection Algorithm in Learning to Rank (Abstract)
  Federico Marcuzzi, Claudio Lucchese, Salvatore Orlando