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Recommender systems for sustainabili...

RecSoGood (Workshop) (2024 :)

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Recommender systems for sustainability and social good = first International Workshop, RecSoGood 2024, Bari, Italy, October 18, 2024 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Recommender systems for sustainability and social good/ edited by Ludovico Boratto ... [et al.].
其他題名:	first International Workshop, RecSoGood 2024, Bari, Italy, October 18, 2024 : proceedings /
其他題名:	RecSoGood 2024
其他作者:	Boratto, Ludovico.
團體作者:	RecSoGood (Workshop)
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	x, 162 p. :ill. (some col.), digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Recommender systems (Information filtering) - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-031-87654-7
ISBN:	9783031876547

Recommender systems for sustainability and social good = first International Workshop, RecSoGood 2024, Bari, Italy, October 18, 2024 : proceedings /
Recommender systems for sustainability and social goodfirst International Workshop, RecSoGood 2024, Bari, Italy, October 18, 2024 : proceedings /[electronic resource] :RecSoGood 2024edited by Ludovico Boratto ... [et al.]. - Cham :Springer Nature Switzerland :2025. - x, 162 p. :ill. (some col.), digital ;24 cm. - Communications in computer and information science,24701865-0937 ;. - Communications in computer and information science ;2470..

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.

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.

ISBN: 9783031876547

Standard No.: 10.1007/978-3-031-87654-7doiSubjects--Topical Terms:

3221329
Recommender systems (Information filtering)
--Congresses.

LC Class. No.: ZA3084

Dewey Class. No.: 005.56

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