The recommender system is widely used in the field of e-commerce and plays an important role in guiding customers to make smart decisions. Although many algorithms are available in the recommender system, collaborative filtering is still one of the most used and successful recommendation technologies. In collaborative filtering, similarity calculation is the main issue. In order to improve the accuracy and quality of recommendations, we proposed an improved similarity model, which takes three impact factors of similarity into account to minimize the deviation of similarity calculation. Compared with the traditional similarity measure, the advantages of our proposed model are that it makes full use of rating data and solves the problem of co-rated items. To validate the efficiency of the proposed algorithm, experiments were performed on four datasets. Results show that the proposed method can effectively improve the preferences of the recommender system and it is suitable for the sparsity data.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6152957 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0204003 | PLOS |
Publication Analysis
Top Keywords
Similar Publications
A study on the detection of conductor quantity in cable cores based on YOLO-cable.
Sci Rep
December 2024
College of Electrical Engineering, Anhui Polytechnic University, Wuhu, 241000, Anhui, China.
The quantity of cable conductors is a crucial parameter in cable manufacturing, and accurately detecting the number of conductors can effectively promote the digital transformation of the cable manufacturing industry. Challenges such as high density, adhesion, and knife mark interference in cable conductor images make intelligent detection of conductor quantity particularly difficult. To address these challenges, this study proposes the YOLO-cable model, which is an improvement made upon the YOLOv10 model.
View Article and Find Full Text PDFCollaborative optimization of signals and ecological driving speed guidance for buses without dedicated bus lanes in the connected environment.
Sci Rep
December 2024
School of Civil Engineering, Henan University of Technology, Zhengzhou, 450001, China.
The transit signal priority, as an effective method to address public transport operation issues, has been widely applied. With the continuous advancement of connected technology, research on developing transit signal priority strategies using vehicle-to-everything technology is gaining increasing attention. However, current traffic signal priority studies primarily focus on optimizing bus speeds on dedicated bus lanes, neglecting the adverse impacts of private vehicle queuing on priority strategies, as well as the carbon emissions resulting from speed fluctuations.
View Article and Find Full Text PDFHybrid rice optimization algorithm inspired grey wolf optimizer for high-dimensional feature selection.
Sci Rep
December 2024
Wuhan Fiberhome Technical Services Co., Ltd, Wuhan, 430205, China.
Feature selection (FS) is a significant dimensionality reduction technique, which can effectively remove redundant features. Metaheuristic algorithms have been widely employed in FS, and have obtained satisfactory performance, among them, grey wolf optimizer (GWO) has received widespread attention. However, the GWO and its variants suffer from limited adaptability, poor diversity, and low accuracy when faced with high-dimensional data.
View Article and Find Full Text PDFPerceptual filters: Exploring disability and ableism's cognitive framework.
J Family Med Prim Care
November 2024
Department of Anesthesiology, All India Institute of Medical Sciences, Gorakhpur, Uttar Pradesh, India.
Ableism, akin to other forms of discrimination such as sexism and racism, is increasingly recognized as a pervasive societal concern directed towards individuals with disabilities. This scholarly inquiry delineates the operational definition, manifestations, and ramifications of ableism, with a specific focus on its manifestations within healthcare settings. It underscores the critical need for targeted interventions aimed at mitigating biases among healthcare professionals and promoting inclusivity within healthcare delivery systems.
View Article and Find Full Text PDFPlastic pollution and marine mussels: Unravelling disparities in research efforts, biological effects and influences of global warming.
Sci Total Environ
December 2024
Université de Lille, CNRS, Université du Littoral Côte d'Opale, IRD, UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, Station marine de Wimereux, F-59000 Lille, France; Department of Marine Resources and Energy, Tokyo University of Marine Science and Technology, 4-5-7 Konan, Minato-ku, Tokyo 108-8477, Japan; Department of Zoology and Entomology, Rhodes University, Grahamstown 6140, South Africa.
The ever-growing contamination of the environment by plastics is a major scientific and societal concern. Specifically, the study of microplastics (1 μm to 5 mm), nanoplastics (< 1 μm), and their leachates is a critical research area as they have the potential to cause detrimental effects, especially when they impact key ecological species. Marine mussels, as ecosystem engineers and filter feeders, are particularly vulnerable to this type of pollution.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!