[HTML][HTML] Similarity measures for Collaborative Filtering-based Recommender Systems: Review and experimental comparison
F Fkih - Journal of King Saud University-Computer and …, 2022 - Elsevier
Collaborative Filtering (CF) filters the flow of data that can be recommended, by a
Recommender System (RS), to a target user according to his taste and his preferences. The …
Recommender System (RS), to a target user according to his taste and his preferences. The …
Survey of similarity functions on neighborhood-based collaborative filtering
H Khojamli, J Razmara - Expert Systems with Applications, 2021 - Elsevier
Today, recommender systems play a vital role in the acceleration of searches by internet
users to find what they are interested in. Among the strategies proposed for recommender …
users to find what they are interested in. Among the strategies proposed for recommender …
Tranexamic acid for the prevention and treatment of bleeding in surgery, trauma and bleeding disorders: a narrative review
A Ockerman, T Vanassche, M Garip, C Vandenbriele… - Thrombosis …, 2021 - Springer
Objectives We review the evidence for tranexamic acid (TXA) for the treatment and
prevention of bleeding caused by surgery, trauma and bleeding disorders. We highlight …
prevention of bleeding caused by surgery, trauma and bleeding disorders. We highlight …
RBPR: A hybrid model for the new user cold start problem in recommender systems
J Feng, Z Xia, X Feng, J Peng - Knowledge-Based Systems, 2021 - Elsevier
The recommender systems aim to predict potential demands of users by analyzing their
preferences and provide personalized recommendation services. User preferences can be …
preferences and provide personalized recommendation services. User preferences can be …
A comparative analysis of similarity measures akin to the Jaccard index in collaborative recommendations: empirical and theoretical perspective
V Verma, RK Aggarwal - Social Network Analysis and Mining, 2020 - Springer
Jaccard index, originally proposed by Jaccard (Bull Soc Vaudoise Sci Nat 37: 241–272,
1901), is a measure for examining the similarity (or dissimilarity) between two sample data …
1901), is a measure for examining the similarity (or dissimilarity) between two sample data …
Improving neighbor-based collaborative filtering by using a hybrid similarity measurement
Memory-based collaborative filtering is one of the recommendation system methods used to
predict a user's rating or preference by exploring historic ratings, but without incorporating …
predict a user's rating or preference by exploring historic ratings, but without incorporating …
User profile correlation-based similarity (UPCSim) algorithm in movie recommendation system
Collaborative filtering is one of the most widely used recommendation system approaches.
One issue in collaborative filtering is how to use a similarity algorithm to increase the …
One issue in collaborative filtering is how to use a similarity algorithm to increase the …
Enhancing recommendation systems performance using highly-effective similarity measures
Abstract In Recommendation Systems (RS) and Collaborative Filtering (CF), the similarity
measures have been the operating component upon which CF performance is essentially …
measures have been the operating component upon which CF performance is essentially …
An improved product recommendation method for collaborative filtering
Collaborative filtering (CF) is the most commonly used technique for online
recommendations. CF works by computing the interests of a user by gathering preferences …
recommendations. CF works by computing the interests of a user by gathering preferences …
An improved collaborative filtering method based on similarity
J Feng, X Fengs, N Zhang, J Peng - PloS one, 2018 - journals.plos.org
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 …
role in guiding customers to make smart decisions. Although many algorithms are available …