LEADER 03817nam 22005655 450 001 9910993937703321 005 20250408165859.0 010 $a3-031-87654-7 024 7 $a10.1007/978-3-031-87654-7 035 $a(CKB)38280507800041 035 $a(DE-He213)978-3-031-87654-7 035 $a(MiAaPQ)EBC32004591 035 $a(Au-PeEL)EBL32004591 035 $a(EXLCZ)9938280507800041 100 $a20250408d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRecommender Systems for Sustainability and Social Good $eFirst International Workshop, RecSoGood 2024, Bari, Italy, October 18, 2024, Proceedings /$fedited by Ludovico Boratto, Allegra De Filippo, Elisabeth Lex, Francesco Ricci 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (X, 162 p. 35 illus., 32 illus. in color.) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v2470 311 08$a3-031-87653-9 327 $a -- 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. 330 $aThis CCIS post conference volume constitutes the proceedings of the First International Workshop on Recommender Systems for Sustainability and Social Good, RecSoGood 2024, in Bari, Italy, in October 2024. The 8 full papers and 6 short papers included in this book were carefully reviewed and selected from 35 submissions. They cover all aspects of Recommender Systems for Sustainable Development Goals; Energy and Carbon Efficiency; and conceptualizations of diversity. 410 0$aCommunications in Computer and Information Science,$x1865-0937 ;$v2470 606 $aData protection$xLaw and legislation 606 $aArtificial intelligence 606 $aPrivacy 606 $aArtificial Intelligence 615 0$aData protection$xLaw and legislation. 615 0$aArtificial intelligence. 615 14$aPrivacy. 615 24$aArtificial Intelligence. 676 $a005.8 676 $a323.448 702 $aBoratto$b Ludovico$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDe Filippo$b Allegra$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLex$b Elisabeth$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRicci$b Francesco$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910993937703321 996 $aRecommender Systems for Sustainability and Social Good$94374367 997 $aUNINA