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ORCID12th IIR 2022: Milan, Italy
- Gabriella Pasi, Paolo Cremonesi, Salvatore Orlando, Markus Zanker, David Massimo, Gloria Turati:
Proceedings of the 12th Italian Information Retrieval Workshop 2022, Milan, Italy, June 29-30, 2022. CEUR Workshop Proceedings 3177, CEUR-WS.org 2022
Invited Talks
- Nicola Tonellotto:
Pseudo-Relevance Feedback in the Era of Dense Retrieval. - Marko Tkalcic:
From Implicit Data to Cognitive Models for Recommender Systems.
Accepted Papers
- Giovanni Toto, Emanuele Di Buccio:
A Modular Approach to Topic Modeling for Heterogeneous Documents. - Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Alberto Carlo Maria Mancino:
Addressing Privacy in Recommender Systems with Federated Learning. - Pasquale Lops, Marco Di Ciano, Nicola Lopane, Lucia Siciliani, Vincenzo Taccardi, Eleonora Ghizzota, Giovanni Semeraro:
AI-based Decision Support Systems for the Management of E-rocurement Procedures. - Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Francesco Maria Donini, Vincenzo Paparella, Claudio Pomo:
An Analysis of Local Explanation with LIME-RS. - Emanuele Cavenaghi, Lorenzo Camaione, Paolo Minasi, Gabriele Sottocornola, Fabio Stella, Markus Zanker:
An Analysis of User Click Behaviour in Online Hotel Search. - Guglielmo Faggioli, Stefano Marchesin:
Assessing the Semantic Difficulty of Queries. - Naieme Hazrati, Francesco Ricci:
Choice Models for Simulating the Consumption of Recommendations. - Guglielmo Faggioli, Nicola Ferro:
Comparing ANOVA Approaches to Detect Significantly Different IR Systems. - Maurizio Ferrari Dacrema, Nicolò Felicioni, Paolo Cremonesi:
Evaluating Recommendations in a User Interface With Multiple Carousels. - Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini, Nicola Ferro, Guglielmo Faggioli, Paolo Cremonesi:
Feature Selection via Quantum Annealers for Ranking and Classification Tasks. - Hanif Emamgholizadeh, Francesco Ricci:
Group Dynamic and Group Recommender Systems for Decision Support. - Alberto Purpura, Gianmaria Silvello, Gian Antonio Susto:
Learning to Rank from Relevance Judgments Distributions. - David Massimo, Francesco Ricci:
Inverse Reinforcement Learning and Point of Interest Recommendations. - Giacomo Balloccu, Ludovico Boratto, Gianni Fenu, Mirko Marras:
Recency, Popularity, and Diversity of Explanations in Knowledge-based Recommendation. - Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Paolo Cremonesi:
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. - Ahtsham Manzoor, Dietmar Jannach:
Revisiting Retrieval-based Approaches for Conversational Recommender Systems. - Pavel Merinov, David Massimo, Francesco Ricci:
Sustainability driven Recommender Systems. - Elias Bassani:
Towards an Information Retrieval Evaluation Library.
Extended Abstracts
- Domenico Dato, Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto:
A Comprehensive Dataset for Modern Learning to Rank Solutions (Abstract). - Veronica Gil-Costa, Fernando Loor, Romina Molina, Franco Maria Nardini, Raffaele Perego, Salvatore Trani:
Energy-Efficient Ranking on FPGAs through Ensemble Model Compression (Abstract). - Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Alberto Veneri:
Interpretable Ranking Using LambdaMART (Abstract). - Federico Marcuzzi, Claudio Lucchese, Salvatore Orlando:
SOUR an Outliers Detection Algorithm in Learning to Rank (Abstract).
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