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46 Citations
A Fuzzy Preference Tree-Based Recommender System for Personalized Business-to-Business E-Services
- Computer ScienceIEEE Transactions on Fuzzy Systems
- 2015
Experimental results show that the proposed fuzzy tree-structured user preference profile reflects user preferences effectively and the recommendation approach demonstrates excellent performance for tree- Structured items, especially in e-business applications.
Fuzzy user-interest drift detection based recommender systems
- Computer Science2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
- 2016
A fuzzy user-interest drift detection based recommender system that adapts to user- interest drift and improves prediction accuracy and the results show that the proposed approach improves the performance of recommender systems in metric of MAE.
Application of Trace-Based Subjective Logic to User Preferences Modeling
- Computer ScienceLPAR
- 2015
The originality of this explorative research is to associate Subjective Logic (SL) to system’s traces (historical information) in order to model the user preferences that improve the decision process.
Personalized Business to Business E-services using Tree-based Recommender System
- Computer Science
- 2016
A method for modelling fuzzy tree-structured user preferences, in which fuzzy set techniques are used to express user preferences is proposed, which is tested and validated using an Australian business dataset and the Movie Lens dataset.
Evaluation of User Model Using Partial Order Relation
- Computer Science2012 IEEE 12th International Conference on Computer and Information Technology
- 2012
An evaluation framework on performance of priority in user model is introduced, and the similarity calculation method of interest structure is designed and shows that the proposed method is more successful than traditional method in the measurement of interest priority.
Modeling Personalized Recommendations of Unvisited Tourist Places Using Genetic Algorithms
- Computer ScienceDNIS
- 2015
A novel approach based on Genetic Algorithm (GA) to model the interest of user for unvisited location and the recommendation results are comparable with matrix factorization based approach and shows improvement of 4.1 % on average root mean squared error (RMSE).
Modeling Missing Data Based on Neural Fuzzy Inference for Implicit Recommendation
- Computer Science2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI)
- 2019
This paper proposes Neural Fuzzy Inference based on User preference and Item popularity (UI-NFI) algorithm to model the missing data in implicit recommendation and uses fuzzy set theory to represent user preference and item popularity that get from the history interactions and side information.
Incorporating Content and Context in Recommender Systems
- Computer Science
- 2015
To improve recommendation quality in the face of incomplete data, this work proposes several novel approaches for incorporating all available data into collaborative filtering algorithms.
Collaborative Filtering Using Restricted Boltzmann Machine and Fuzzy C-means
- Computer Science
- 2018
An attempt is made to cluster the users using FCM clustering algorithm, and then, RBM is used to predict the user’s preferences and the results depict the performance of using both FCM and RBM to build the model for recommendation.
Comprehensive fuzzy tree based recommended System for Search Engine
- Computer Science
- 2015
The experimental result on the dataset proves that the proposed methodology using fuzzy tree-structured user preference enables a valid demonstration on tree- Structured items mainly in e-business applications.
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