Search Results for author:
Found 5 papers, 0 papers with code
Presentation a Trust Walker for rating prediction in Recommender System with Biased Random Walk: Effects of H-index Centrality, Similarity in Items and Friends
Also, for this problem, researchers use different modes of the Random Walk algorithm to randomly visit some users, study their behavior, and gain the degree of trust between them.
A Novel Community Detection Based Genetic Algorithm for Feature Selection
The findings indicate that the new approach continuously yields improved classification accuracy.
Review of Swarm Intelligence-based Feature Selection Methods
In this paper, a comparative analysis of different feature selection methods is presented, and a general categorization of these methods is performed.
Presentation of a Recommender System with Ensemble Learning and Graph Embedding: A Case on MovieLens
Graph embedding was also proposed for resolution of this issue, where all or part of user behavior can be simulated through the generation of several vectors, resolving the problem of user behavior analysis to a large extent while maintaining high efficiency.
Integration of graph clustering with ant colony optimization for feature selection
In the second step, the features are divided into several clusters using a community detection algorithm and finally in the third step, a novel search strategy based on the ant colony optimization is developed to select the final subset of features.
