Results 71 to 80 of about 7,593,003 (291)

Alleviating Cold Start in the EOSC Recommendations: Extended Page Rank Algorithm

IEEE Access
Recommender systems are becoming crucial in academia, where the number of available scientific resources is continuously increasing. One of the main challenges of such systems is a cold start problem, which often occurs when new users have no preference ...
Marcin Wolski, Antoni Klorek, Anna Kobusinska   +2 more
doaj   +1 more source

A Noninvasive Approach to Study Localized Forces in 3D Epithelia

Advanced Materials, EarlyView.
Epithelial morphogenesis depends on dynamic mechanical coupling between adhesion complexes and the cytoskeleton, yet its regulation in polarized 3D tissues remains elusive. We developed a noninvasive strategy using cell‐like elastic microbeads to quantify local forces in intact epithelia.
Niels Gouirand, Muhamet Ibrahimi, Claire Valotteau, Brice Lecouffe, André Le Bivic, Dominique Massey‐Harroche, Felix Rico, Matthias Merkel, Delphine Delacour, Elsa Bazellières   +9 more
wiley   +1 more source

Large Language Model Driven User Cold Start Recommendations [PDF]

The advent of new and powerful LLM models has given rise to innovative approaches to using large language models and recommendation systems. These models have been trained on a large corpus of data and world knowledge, which can be harnessed in ...
Dalvi, Shubham Prabhakar
core   +2 more sources

Photocatalytic Water Splitting on the Lunar Surface: Prospects for In Situ Resource Utilization

Advanced Materials Interfaces, EarlyView.
Water has been found in craters on the moon nearby locations which are illuminated >80% of the time. Photocatalysis uses energy from sunlight to drive chemical reactions such as water splitting to produce oxygen and hydrogen. It is a scalable technology that requires lighter equipment and utilizes resources available on the moon. ABSTRACT The discovery
Ranjani Kalyan, Thomas D. Small, Gregory F. Metha, Mahmoud Adel Hamza, Thomas J. O'Dea, Yideng Shen, Cameron J. Shearer   +6 more
wiley   +1 more source

Smart‐Release Ion‐Exchanged Ca‐Montmorillonite for Corrosion Protection of AA2024 Aluminium Alloy

Advanced Materials Interfaces, EarlyView.
Smart‐release anticorrosion pigments based on Zn‐ and Mn‐modified montmorillonite were developed by ion exchange of Ca‐montmorillonite and evaluated for the protection of AA2024 aluminium alloy in artificial acid rain. Both modified pigments provided effective corrosion inhibition, with Zn‐modified montmorillonite (Zn‐MMT) achieving an inhibition ...
Sergiy Korniy, Mariia Olena Danyliak, Ivan Zin   +2 more
wiley   +1 more source

IPTV program recommendation based on combination strategies

MATEC Web of Conferences, 2018
As a new interactive service technology, IPTV has been extensively studying in the field of TV pro-gram recommendation, but the sparse of the user-program rating matrix and the cold-start problem is a bottleneck that the program recommended accurately ...
Li Hao, Xia Huan, Kang Yan, Uddin Mohammad Nashir   +3 more
doaj   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

Advanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Content-Aware Few-Shot Meta-Learning for Cold-Start Recommendation on Portable Sensing Devices

Sensors
The cold-start problem in sequence recommendations presents a critical and challenging issue for portable sensing devices. Existing content-aware approaches often struggle to effectively distinguish the relative importance of content features and ...
Xiaomin Lv, Kai Fang, Tongcun Liu
doaj   +1 more source

ML2E: Meta-Learning Embedding Ensemble for Cold-Start Recommendation

IEEE Access, 2020
Cold-start problem has been recognized as the most crucial challenge in recommender systems. Many recommendation algorithms work well when lots of preference information is available but start to degrade in cold-start settings.
Huiwei Wang, Yong Zhao
doaj   +1 more source

Cold & Warm Net: Addressing Cold-Start Users in Recommender Systems

, 2023
Cold-start recommendation is one of the major challenges faced by recommender systems (RS). Herein, we focus on the user cold-start problem. Recently, methods utilizing side information or meta-learning have been used to model cold-start users.
Tan, Xianfeng, Zhang, Zehao, Kuang, Zongqiang, Zhang, Xiangyu, Huang, Fan   +4 more
core