Mostrando ítems 1-17 de 17

    • A Collaborative Filtering Probabilistic Approach for Recommendation to Large Homogeneous and Automatically Detected Groups 

      Bobadilla, Jesús; Gutiérrez, Abraham; Alonso, Santiago; Hurtado, Remigio (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2020)
      In the collaborative filtering recommender systems (CFRS) field, recommendation to group of users is mainly focused on stablished, occasional or random groups. These groups have a little number of users: relatives, friends, ...
    • Agente conversacional para búsqueda y recomendación de ofertas laborales 

      Gómez-Loizaga, Héctor Antonio (18/09/2019)
      El objetivo del presente trabajo es el desarrollo de la arquitectura y metodología utilizada por un agente conversacional para interaccionar con un usuario y extraer la información necesaria que le permita actuar como ...
    • An Adapted Approach for User Profiling in a Recommendation System: Application to Industrial Diagnosis 

      Taghezout, Noria; Benkaddour, Fatima Zohra; Kaddour-Ahmed, Fatima Zahra; Hammadi, Ilyes-Ahmed (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 12/2018)
      In this paper, we propose a global architecture of a recommender tool, which represents a part of an existing collaborative platform. This tool provides diagnostic documents for industrial operators. The recommendation ...
    • An Effective Tool for the Experts' Recommendation Based on PROMETHEE II and Negotiation: Application to the Industrial Maintenance 

      Houari, Nawal Sad; Taghezout, Noria (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2021)
      In this article, we propose an expert recommendation tool that relies on the skills of experts and their interventions in collaboration. This tool provides us with a list of the most appropriate (effective) experts to solve ...
    • Attentive Flexible Translation Embedding in Top-N Sparse Sequential Recommendations 

      Seo, Min-Ji; Kim, Myung-Ho (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 12/2023)
      Sequential recommendation aims to predict the user’s next action based on personal action sequences. The major challenge in this task is how to achieve high performance recommendation under the data sparsity problem. ...
    • Classification-based Deep Neural Network Architecture for Collaborative Filtering Recommender Systems 

      Bobadilla, Jesús; Ortega, Fernando; Gutiérrez, Abraham; Alonso, Santiago (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 03/2020)
      This paper proposes a scalable and original classification-based deep neural architecture. Its collaborative filtering approach can be generalized to most of the existing recommender systems, since it just operates on the ...
    • Comprehensive Evaluation of Matrix Factorization Models for Collaborative Filtering Recommender Systems 

      Bobadilla, Jesús; Dueñas-Lerín, Jorge; Ortega, Fernando; Gutiérrez, Abraham (International Journal of Interactive Multimedia and Artificial Intelligence, 04/2023)
      Matrix factorization models are the core of current commercial collaborative filtering Recommender Systems. This paper tested six representative matrix factorization models, using four collaborative filtering datasets. ...
    • DeepFair: Deep Learning for Improving Fairness in Recommender Systems 

      Bobadilla, Jesús; Lara-Cabrera, Raúl; González-Prieto, Ángel; Ortega, Fernando (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2021)
      The lack of bias management in Recommender Systems leads to minority groups receiving unfair recommendations. Moreover, the trade-off between equity and precision makes it difficult to obtain recommendations that meet both ...
    • Local Model-Agnostic Explanations for Black-box Recommender Systems Using Interaction Graphs and Link Prediction Techniques 

      Caro-Martínez, Marta; Jiménez-Díaz, Guillermo; Recio-García, Juan A. (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2023)
      Explanations in recommender systems are a requirement to improve users’ trust and experience. Traditionally, explanations in recommender systems are derived from their internal data regarding ratings, item features, and ...
    • Neural Collaborative Filtering Classification Model to Obtain Prediction Reliabilities 

      Bobadilla, Jesús; Gutiérrez, Abraham; Alonso, Santiago; González-Prieto, Ángel (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2022)
      Neural collaborative filtering is the state of art field in the recommender systems area; it provides some models that obtain accurate predictions and recommendations. These models are regression-based, and they just return ...
    • OntoInfoG++: A Knowledge Fusion Semantic Approach for Infographics Recommendation 

      Deepak, Gerard; Vibakar, Adithya; Santhanavijayan, A. (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2023)
      As humans tend to improvise and learn on a constant basis, the need for visualizing and recommending knowledge is increasing. Since the World Wide Web is exploded with a lot of multimedia content and with a growing amount ...
    • Promoting Social Media Dissemination of Digital Images Through CBR-Based Tag Recommendation 

      Martín-Gómez, Lucía; Pérez-Marcos, Javier; Cordero-Gutiérrez, Rebeca; De La Iglesia, Daniel H. (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 09/2022)
      Multimedia content has become an essential tool to share knowledge, sell products or disseminate messages. Some social networks use multimedia content to promote information and create social communities. In order to ...
    • Review of Current Student-Monitoring Techniques used in eLearning-Focused recommender Systems and Learning analytics. The Experience API & LIME model Case Study 

      Corbi, Alberto; Burgos, Daniel (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 09/2014)
      Recommender systems require input information in order to properly operate and deliver content or behaviour suggestions to end users. eLearning scenarios are no exception. Users are current students and recommendations ...
    • Sistema de recomendación para nuevos usuarios de Airbnb 

      Pardo-Cuesta, Raquel (23/07/2019)
      Las recomendaciones de productos para nuevos usuarios de una compañía, problema conocido como cold start, supone nuevos métodos de inteligencia artificial para poder llevar a cabo la recomendación de un producto con ...
    • Social Relations and Methods in Recommender Systems: A Systematic Review 

      Medel, Diego; González-González, Carina; V. Aciar, Silvana (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2022)
      With the constant growth of information, data sparsity problems, and cold start have become a complex problem in obtaining accurate recommendations. Currently, authors consider the user's historical behavior and find ...
    • Testing Deep Learning Recommender Systems Models on Synthetic GAN-Generated Datasets 

      Bobadilla, Jesús; Gutiérrez, Abraham (International Journal of Interactive Multimedia and Artificial Intelligence, 10/2023)
      The published method Generative Adversarial Networks for Recommender Systems (GANRS) allows generating data sets for collaborative filtering recommendation systems. The GANRS source code is available along with a representative ...
    • Using Recommendation System for E-learning Environments at degree level 

      Sanjuán Martínez, Óscar; Pelayo García-Bustelo, B. Cristina; González-Crespo, Rubén; Torres Franco, Enrique (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 12/2009)
      Nowadays, new technologies and the fast growth of the Internet have made access to information easier for all kind of people, raising new challenges to education when using Internet as a medium. One of the best examples ...