Recommender Systems for Sustainability and Social Good

First International Workshop, RecSoGood 2024, Bari, Italy, October 18, 2024, Proceedings

AvLudovico Boratto,Allegra De Filippo

Häftad, Engelska, 2025

Del 2470 i serien Communications in Computer and Information Science

887 kr

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Beskrivning

This CCIS post conference volume constitutes the proceedings of the First International Workshop on Recommender Systems for Sustainability and Social Good, RecSoGood 2024, in Bari, Italy, in October 2024.The 8 full papers and 6 short papers included in this book were carefully reviewed and selected from 35 submissions. They cover all aspects of Recommender Systems for Sustainable Development Goals; Energy and Carbon Efficiency; and conceptualizations of diversity.

Produktinformation

Utgivningsdatum:2025-04-09
Mått:155 x 235 x 10 mm
Vikt:271 g
Format:Häftad
Språk:Engelska
Serie:Communications in Computer and Information Science
Antal sidor:162
Förlag:Springer International Publishing AG
ISBN:9783031876530

Utforska kategorier

Artificiell intelligens inom Data och IT
IT-säkerhet inom Data och IT

Innehållsförteckning

.- Sustainable Development Goals; Energy and Carbon Efficiency; and conceptualizations of diversity...- Decoupled Recommender Systems: Exploring Alternative Recommender Ecosystem Designs..- Enhancing Tourism Recommender Systems for Sustainable City Trips Using Retrieval-Augmented Generation..- Simulating the Impact of Recommendation Salience on Tourists Experienced Utility..- Knowledge Data Modeling in Food Recommendation: A Case Study on Nutritional Values..- Modeling Social Media Recommendation Impacts Using Academic Networks: A Graph Neural Network Approach..- Green Recommender Systems: Optimizing Dataset Size for Energy-Efficient Algorithm Performance..- EMERS: Energy Meter for Recommender Systems..- e-Fold Cross-Validation for Recommender-System Evaluation..- RecSys CarbonAtor: Predicting Carbon Footprint of Recommendation System Models..- Eco-Aware Graph Neural Networks for Sustainable Recommendations..- 14 Kg of CO2: Analyzing the Carbon Footprint and Performance of Session-Based Recommendation Algorithms..- From Explanation to Exploration: promoting DivErsity in Recommendation Systems..- Effects of Representation Nudges on the Perception of Playlist Recommendations.

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