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Network Resource Personalized Recommendation System Based on Collaborative Filtering Algorithm
Several existing personalized recommendation systems for network resources do not specifically classify user history information personalized...
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Collaborative Filtering Based on Rough C-Means Clustering with Missing Value Processing
A significant problem in collaborative filtering (CF) tasks is that the data often contains many missing values. Conventional rough clustering-based...
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Popularity Bias in Collaborative Filtering-Based Multimedia Recommender Systems
Multimedia recommender systems suggest media items, e.g., songs, (digital) books and movies, to users by utilizing concepts of traditional...
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New hybrid semantic-based collaborative filtering recommender systems
The recommender system (RS) improves the users’ experience when searching for and buying items by providing recommendations. This paper presents a...
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Semi-supervised collaborative filtering ensemble
Collaborative filtering (CF) plays a central role in recommender systems, but often suffers from the data sparsity issue that dramatically degrades...
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Relationship between diversity of collaborative group members’ race and ethnicity and the frequency of their collaborative contributions in GitHub
Online collaborative platforms provide an environment for diverse developers to collaborate together in Open Source Software (OSS) projects. Previous...
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Multimodal collaborative graph for image recommendation
Recent works for personalized recommendation typically emphasize their efforts on learning users’ interests from interactions. However, users make...
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Time-Aware QoS Web Service Selection Using Collaborative Filtering: A Literature Review
The large increase in the number of available Web services makes the selection of suitable services a big challenge. Several methods have been...
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CF-PMSS: Collaborative Filtering Based on Preference Model and Sparrow Search
Collaborative filtering (CF) is a widely used recommendation method that can be evaluated according to the rating prediction or top-N...
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Joint Locality Preservation and Adaptive Combination for Graph Collaborative Filtering
Due to its powerful representation ability, Graph Convolutional Network (GCN) based collaborative filtering (CF), which treats the interaction of...
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Decentralized Collaborative Filtering Algorithm with Privacy Preserving for Recommendation in Mobile Edge Computing
Mobile edge computing (MEC) deploys network services closer to the user’s wireless access network side and provides IT service environment and cloud...
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A Hybrid Framework Using Natural Language Processing and Collaborative Filtering for Performance Efficient Feedback Mining and Recommendation
Product development insights may be found through user reviews on App stores, product forums, and social media. This feedback is often regarded as...
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Tag-Extended Collaborative Filtering Recommendation Algorithm
For most of recommendation algorithms that use the relationship between tags, users, and items have to face the problem of tag sparse. Aiming at the...
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Fast and Accurate Evaluation of Collaborative Filtering Recommendation Algorithms
Collaborative filtering are recommender systems algorithms that provide personalized recommendations to users in various online environments such as...
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Smart Learning Objects Retrieval for E-Learning with Contextual Recommendation based on Collaborative Filtering
With the increase in Technology Enhanced Learning (TEL), the effective retrieval and availability of Learning Objects (LOs) for course designers is a...
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Integrating metadata into deep autoencoder for handling prediction task of collaborative recommender system
Nowadays, Deep learning (DL) techniques have been proven successful as learning techniques in various research fields ranging from computer vision to...
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Simplifying Knowledge-Aware Aggregation for Knowledge Graph Collaborative Filtering
Incorporating knowledge graph (KG) for recommendation has been well considered in recent researches since it can alleviate the sparsity and...
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Stability and Generalization of Hypergraph Collaborative Networks
Graph neural networks have been shown to be very effective in utilizing pairwise relationships across samples. Recently, there have been several...
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A user-based video recommendation approach using CAC filtering, PCA with LDOS-CoMoDa
Context-aware collaborative filtering is an efficient method for tailoring recommendations to the individual contextual settings of users, with the...
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Design and Application of Japanese MOOC Teaching Resources System Based on User Collaborative Filtering Recommendation Algorithm
The core of personalized recommendation is an algorithm, which searches for a group of users with similar interests to the target user as “nearest...