People-to-People Reciprocal Recommenders

Koprinska, Irena; Yacef, Kalina

doi:10.1007/978-1-0716-2197-4_11

Cited by 3 publications

(4 citation statements)

References 34 publications

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“…Recommender systems are an established technology in different people to people (P2P) recommendation scenarios-examples thereof are recommending new friends in social networks, recommending business partnerships, and recommending jobs Koprinska and Yacef, 2022). Finding the right job is crucial for a further personal development and a productive employment.…”

Section: Decent Work and Economic Growthmentioning

confidence: 99%

“…A specific task is to assure an increasing support for developing countries to assure an equitable progress for all and also strengthen the path toward sustainability. Identifying and establishing such cooperations can also be supported by recommender systems, for example, people-2-people recommender systems can support the identification of business partners and research cooperations (Hu and Ma, 2021;Koprinska and Yacef, 2022).…”

Section: Partnerships For the Goalsmentioning

confidence: 99%

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Reviews in Recommender Systems: 2022

2024

Frontiers Research Topics

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Frontiers is more than just an open access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers journal seriesThe Frontiers journal series is a multi-tier and interdisciplinary set of openaccess, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. At the same time, the Frontiers journal series operates on a revolutionary invention, the tiered publishing system, initially addressing specific communities of scholars, and gradually climbing up to broader public understanding, thus serving the interests of the lay society, too. Dedication to qualityEach Frontiers article is a landmark of the highest quality, thanks to genuinely collaborative interactions between authors and review editors, who include some of the world's best academicians. Research must be certified by peers before entering a stream of knowledge that may eventually reach the public -and shape society; therefore, Frontiers only applies the most rigorous and unbiased reviews. Frontiers revolutionizes research publishing by freely delivering the most outstanding research, evaluated with no bias from both the academic and social point of view. By applying the most advanced information technologies, Frontiers is catapulting scholarly publishing into a new generation. What are Frontiers Research Topics?Frontiers Research Topics are very popular trademarks of the Frontiers journals series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area.

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Section: Decent Work and Economic Growthmentioning

confidence: 99%

Section: Partnerships For the Goalsmentioning

confidence: 99%

Reviews in Recommender Systems: 2022

2024

Frontiers Research Topics

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“…Recommender systems are an established technology in different people to people (P2P) recommendation scenarios—examples thereof are recommending new friends in social networks, recommending business partnerships, and recommending jobs (Gutiérrez et al, 2019 ; Koprinska and Yacef, 2022 ). Finding the right job is crucial for a further personal development and a productive employment.…”

Section: Recommender Systems For Sustainabilitymentioning

confidence: 99%

Section: Recommender Systems For Sustainabilitymentioning

confidence: 99%

Recommender systems for sustainability: overview and research issues

Felfernig,

Wundara,

Tran

et al. 2023

Front. Big Data

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Sustainability development goals (SDGs) are regarded as a universal call to action with the overall objectives of planet protection, ending of poverty, and ensuring peace and prosperity for all people. In order to achieve these objectives, different AI technologies play a major role. Specifically, recommender systems can provide support for organizations and individuals to achieve the defined goals. Recommender systems integrate AI technologies such as machine learning, explainable AI (XAI), case-based reasoning, and constraint solving in order to find and explain user-relevant alternatives from a potentially large set of options. In this article, we summarize the state of the art in applying recommender systems to support the achievement of sustainability development goals. In this context, we discuss open issues for future research.

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Combined Application of Various Techniques for Personalized Job Recommendation

Dwivedi

Allwani

2023

2023 International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF)

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People-to-People Reciprocal Recommenders

Cited by 3 publications

References 34 publications

Reviews in Recommender Systems: 2022

Reviews in Recommender Systems: 2022

Recommender systems for sustainability: overview and research issues

Combined Application of Various Techniques for Personalized Job Recommendation

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