Results 71 to 80 of about 24,916,518 (300)

Resolving Data Sparsity via Aggregating Graph-Based User–App–Location Association for Location Recommendations

Applied Sciences, 2022
Personalized location recommendations aim to recommend places that users want to visit, which can save their decision-making time in daily life. However, the recommending task faces a serious data sparsity problem because users have only visited a small ...
Xiang Chen, Junxin Chen, Xiaoqin Lian, Weimin Mai   +3 more
doaj   +1 more source

Evidence‐Based Clinical Practice Guidelines for the Management of Pediatric Febrile Neutropenia: Resource‐Sensitive Recommendations for the Asian Continent

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Febrile neutropenia (FN) is a frequent and serious complication in children receiving cancer therapy. Standardizing FN management across Asia is challenging due to variable healthcare infrastructure, diagnostic capacity, and infection patterns; however, it could improve resource use and patient outcomes.
Joliza Patricia Cañeba, Shweta Bansal, Tea Reljic, Allyne Montecillo‐Aguelo, Hamidah Alias, Farrah Amaranto, Maria Stella Aquino‐Calingasan, Bambang Ardianto, Eggi Arguni, Sally Blair, Thi Tam Dang, Maria Beatriz Gepte, Samanmalee Gunasekara, Andini Handayani, Miriam Kimpo, Catherine G. Lam, Nawachai Lertvivatpong, Sergio Licona, Ana Loseo, Ratha Mlis, Vivian Moreno Berrio, Nguyen Hoai Anh, Anna Lisa Ong‐Lim, Ha Thu Pham, Krishna Sagar Sharma, Bun Sereyleak, Sally Jane G. Velasco‐Aro, Su Yadana, Ambuj Kumar, Sheena Mukkada   +29 more
wiley   +1 more source

Correlation Visual Adversarial Bayesian Personalized Ranking Recommendation Model

工程科学与技术, 2022
In order to solve three problems of traditional recommendation models, i.e., data sparsity, low robustness and the lack of deep-level semantics among heterogeneous features, a novel correlation visual adversarial Bayesian personalized ranking (CVABPR ...
Guangli LI, Jianwu ZHUO, Guangxin XU, Chuanxiu LI, Guangting WU, Hongbin ZHANG   +5 more
doaj  

Operation strategy for engineered natural ventilation using machine learning under sparse data conditions

Japan Architectural Review, 2022
Machine learning (ML) is a useful technique for improving building operations. However, if data can only be obtained from a target building, the data shortage will limit the use of general ML models. To overcome this issue, simplified targets and limited
Kyosuke Hiyama, Kenichiro Takeuchi, Yuichi Omodaka, Thanyalak Srisamranrungruang   +3 more
doaj   +1 more source

Multi-scale Mining of fMRI Data with Hierarchical Structured Sparsity [PDF]

2011 International Workshop on Pattern Recognition in NeuroImaging, 2011
Reverse inference, or brain reading, is a recent paradigm for analyzing functional magnetic resonance imaging (fMRI) data based on pattern recognition and statistical learning. By predicting some cognitive variables related to brain activation maps, this approach aims at decoding brain activity.
Jenatton, Rodolphe, Gramfort, Alexandre, Michel, Vincent, Obozinski, Guillaume, Eger, Evelyn, Bach, Francis, Thirion, Bertrand   +6 more
openaire   +4 more sources

Uncovering Inequities: The Role of Social Determinants of Health in Hospitalized Adolescents and Young Adults With Heavy Menstrual Bleeding

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Heavy menstrual bleeding (HMB) is a common condition among adolescents and young adults (AYAs) and is the leading cause of iron deficiency anemia (IDA) in this population. Growing evidence suggests that social determinants of health (SDOH) influence menstrual bleeding patterns, access to care, and treatment. However, no studies have
Maria Carter‐Febres, Cristina Tarango, Ashley Childress, Chunyan Liu, Evan Thomas, Jennifer Pomales, Eric S. Mullins   +6 more
wiley   +1 more source

A Hyperbolic Graph Neural Network Model with Contrastive Learning for Rating–Review Recommendation

Entropy
In recommender systems research, the data sparsity problem has driven the development of hybrid recommendation algorithms integrating multimodal information and the application of graph neural networks (GNNs).
Shuyun Fang, Junling Wang, Fukun Chen
doaj   +1 more source

Diversity and complexity in neural organoids

FEBS Letters, EarlyView.
Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley   +1 more source

Analysis of Scatter SVM sparsity on USPS data.

, 2012
Analysis of Scatter SVM sparsity on USPS data.
Robert Jenssen (124371), Klaus-Robert Müller (52696), Alexander Zien (124376), Marius Kloft (124374), Sören Sonnenburg (86037)   +4 more
core   +1 more source

Advances and Perspectives on Knowledge Transfer Based Cross-Domain Recom-mendation

Jisuanji kexue yu tansuo, 2020
Data sparseness and cold start problems caused by unbalanced data distribution restrict the further development of personalized recommendation systems. With the rise of transfer learning technology, cross-domain recommendation based on transfer learning ...
REN Hao, LIU Baisong, SUN Jinyang
doaj   +1 more source