Zobrazeno 1 - 10
of 25 677
pro vyhledávání: '"Data Sparsity"'
Accurate bicycling volume estimation is crucial for making informed decisions about future investments in bicycling infrastructure. Traditional link-level volume estimation models are effective for motorised traffic but face significant challenges wh
Externí odkaz:
http://arxiv.org/abs/2410.08522
With the rapid growth of digital information, personalized recommendation systems have become an indispensable part of Internet services, especially in the fields of e-commerce, social media, and online entertainment. However, traditional collaborati
Externí odkaz:
http://arxiv.org/abs/2411.06374
Session-based Social Recommendation (SSR) leverages social relationships within online networks to enhance the performance of Session-based Recommendation (SR). However, existing SSR algorithms often encounter the challenge of "friend data sparsity".
Externí odkaz:
http://arxiv.org/abs/2409.02702
Autor:
Massei, Stefano, Saluzzi, Luca
Solving large-scale continuous-time algebraic Riccati equations is a significant challenge in various control theory applications. This work demonstrates that when the matrix coefficients of the equation are quasiseparable, the solution also exhibits
Externí odkaz:
http://arxiv.org/abs/2408.16569
Publikováno v:
Electronic Research Archive. 2024, Vol. 32 Issue 4, p1-17. 17p.
Akademický článek
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Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 9, Pp 102224- (2024)
With the development of artificial intelligence in education, knowledge tracing (KT) has become a current research hotspot and is the key to the success of personalized instruction. However, data sparsity remains a significant challenge in the KT dom
Externí odkaz:
https://doaj.org/article/f262d029c0fb4d1f9796c03cc8ccc987
Autor:
Giannopoulos, Panagiotis G.1 (AUTHOR), Dasaklis, Thomas K.1 (AUTHOR) dasaklis@eap.gr, Rachaniotis, Nikolaos2 (AUTHOR)
Publikováno v:
Scientific Reports. 11/14/2024, Vol. 12 Issue 1, p1-13. 13p.
Publikováno v:
Electronic Research Archive, Vol 32, Iss 4, Pp 2728-2744 (2024)
Point-of-interest (POI) recommendation has attracted great attention in the field of recommender systems over the past decade. Various techniques, such as those based on matrix factorization and deep neural networks, have demonstrated outstanding per
Externí odkaz:
https://doaj.org/article/b5e7a8917e594a29b040cf7f83201b50
Due to the sparsity of user data, sentiment analysis on user reviews in e-commerce platforms often suffers from poor performance, especially when faced with extremely sparse user data or long-tail labels. Recently, the emergence of LLMs has introduce
Externí odkaz:
http://arxiv.org/abs/2403.06139