Using Hierarchical Graph Maps to Explain Collaborative Filtering Recommendations-Reference-Cited by-同舟云学术

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Using Hierarchical Graph Maps to Explain Collaborative Filtering Recommendations

Published:2014-01-31 Issue:5 Volume:29 Page:462-477
ISSN:0884-8173
Container-title:International Journal of Intelligent Systems
language:en
Short-container-title:Int. J. Intell. Syst.

Author:

Ortega Fernando¹,Bobadilla Jesús¹,Hernando Antonio¹,Rodríguez Fernando¹

Affiliation:

1. Universidad Politécnica of Madrid and FilmAffinity.com research team; Madrid Spain

Publisher

Wiley

Subject

Artificial Intelligence,Human-Computer Interaction,Theoretical Computer Science,Software

Reference34 articles.

1. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions;Adomavicius;IEEE Transactions on Knowl Data Eng,2005

2. A multigranular linguistic content-based recommendation model;Martínez;Int J Intell Syst,2007

3. A hybrid trust-enhanced collaborative filtering recommendation approach for personalized government-to-business e-services;Shambour;Int J Intell Syst,2011

4. Cinema screen recommender agent: combining collaborative and content-based filtering;Antonopoulus;IEEE Intell Syst,2006

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1. A New Recommendation Approach Based on Probabilistic Soft Clustering Methods: A Scientific Documentation Case Study;IEEE Access;2019

2. Method to interactively visualize and navigate related information;Expert Systems with Applications;2018-11

3. A probabilistic model for recommending to new cold-start non-registered users;Information Sciences;2017-01

4. Identifying representative users in matrix factorization-based recommender systems: application to solving the content-less new item cold-start problem;Journal of Intelligent Information Systems;2016-06-23

5. What Should I Read Next? A Personalized Visual Publication Recommender System;Lecture Notes in Computer Science;2015

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