Differentiable Ranking Metric Using Relaxed Sorting for Top-K Recommendation

Autor: Hyunsung Lee, Sangwoo Cho, Yeongjae Jang, Jaekwang Kim, Honguk Woo

Publikováno v: IEEE Access, Vol 9, Pp 114649-114658 (2021)

Most recommenders generate recommendations for a user by computing the preference score of items, sorting the items according to the score, and filtering top- $K$ -items of high scores. Since sorting is not differentiable and is difficult to optimize

Externí odkaz: https://doaj.org/article/3a791681a99e44d590c369455ba486e1

Influence of varying potassium levels on yield, water productivity, profitability and resource-use efficiency in kharif mungbean (Vigna radiata) under semi-arid conditions of Afghanistan

Autor: HAMDULLAH HAMIM, ANIL K CHOUDHARY

Publikováno v: The Indian Journal of Agricultural Sciences, Vol 89, Iss 3 (2019)

The application of K2O @ 80 kg/ha could be used as blanket recommendation for obtaining higher productivity, profitability as well as higher resource-use efficiency in kharif mungbean. As a site-specific precision recommendation, the economic optimum

Externí odkaz: https://doaj.org/article/f3ff1179d694456ba213fd87fe716e48

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Novel Scheme for Movie Recommendation System Using User Similarity and Opinion Mining: A Recent Study

Autor: A. Pethalakshmi, R. Nagamanjula

The rise of users in a mobile environment has made movie recommender systems an important research issue. This system helps to recommend top-k movies for target user. To help consumers locate the best movies in a more convenient way, a complete aggre

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73fa603b42bcad7f1b80b2f20f9fe7d8
https://doi.org/10.9734/bpi/rder/v12/5384d

Equality of Voice: {T}owards Fair Representation in Crowdsourced Top-K Recommendations

Autor: Abhijnan Chakraborty, Patrick Loiseau, Gourab K Patro, Niloy Ganguly, Krishna P. Gummadi

Publikováno v: Proceedings of the 2019 Conference on Fairness, Accountability, and Transparency
Proceedings of the Conference on Fairness, Accountability, and Transparency-FAT* '19
Proceedings of the Conference on Fairness, Accountability, and Transparency-FAT* 19
FAT* 2019-ACM Conference on Fairness, Accountability, and Transparency
FAT* 2019-ACM Conference on Fairness, Accountability, and Transparency, Jan 2019, Atlanta, United States. pp.129-138, ⟨10.1145/3287560.3287570⟩
FAT

To help their users to discover important items at a particular time, major websites like Twitter, Yelp, TripAdvisor or NYTimes provide Top-K recommendations (e.g., 10 Trending Topics, Top 5 Hotels in Paris or 10 Most Viewed News Stories), which rely

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0bc0b9b50efd09627fd6f2d5f4f6112a
https://hdl.handle.net/21.11116/0000-0008-F0BC-521.11116/0000-0005-F70A-A