Volume 12 (2024)
Volume 11 (2023)
Volume 10 (2022)
Volume 9 (2021)
Volume 8 (2020)
Volume 7 (2019)
Volume 6 (2018)
Volume 5 (2017)
Volume 4 (2016)
Volume 3 (2015)
Volume 2 (2014)
Volume 1 (2013)
Increasing Performance of Recommender Systems by Combining Deep Learning and Extreme Learning Machine

Z. Nazari; H.R. Koohi; J. Mousavi

Volume 10, Issue 2 , April 2022, , Pages 185-195

https://doi.org/10.22044/jadm.2022.11248.2279

Abstract
  Nowadays, with the expansion of the internet and its associated technologies, recommender systems have become increasingly common. In this work, the main purpose is to apply new deep learning-based clustering methods to overcome the data sparsity problem and increment the efficiency of recommender systems ...  Read More

Online Recommender System Considering Changes in User's Preference

J. Hamidzadeh; M. Moradi

Volume 9, Issue 2 , April 2021, , Pages 203-212

https://doi.org/10.22044/jadm.2020.9518.2085

Abstract
  Recommender systems extract unseen information for predicting the next preferences. Most of these systems use additional information such as demographic data and previous users' ratings to predict users' preferences but rarely have used sequential information. In streaming recommender systems, the emergence ...  Read More

A Recommendation System for Finding Experts in Online Scientific Communities

S. Javadi; R. Safa; M. Azizi; Seyed A. Mirroshandel

Volume 8, Issue 4 , November 2020, , Pages 573-584

https://doi.org/10.22044/jadm.2020.9087.2045

Abstract
  Online scientific communities are bases that publish books, journals, and scientific papers, and help promote knowledge. The researchers use search engines to find the given information including scientific papers, an expert to collaborate with, and the publication venue, but in many cases due to search ...  Read More