Deep learning with small datasets: using autoencoders to address limited datasets in construction management
Large datasets are necessary for deep learning as the performance of the algorithms used
increases as the size of the dataset increases. Poor data management practices and the low …
increases as the size of the dataset increases. Poor data management practices and the low …
Collaborative filtering recommendation algorithm for MOOC resources based on deep learning
L Wu - Complexity, 2021 - Wiley Online Library
In view of the poor recommendation performance of traditional resource collaborative
filtering recommendation algorithms, this article proposes a collaborative filtering …
filtering recommendation algorithms, this article proposes a collaborative filtering …
Deep variational matrix factorization with knowledge embedding for recommendation system
Automatic recommendation has become an increasingly relevant problem to industries,
which allows users to discover new items that match their tastes and enables the system to …
which allows users to discover new items that match their tastes and enables the system to …
A collaborative filtering recommender systems: Survey
In the current digital landscape, both information consumers and producers encounter
numerous challenges, underscoring the importance of recommender systems (RS) as a vital …
numerous challenges, underscoring the importance of recommender systems (RS) as a vital …
Multisource heterogeneous user-generated contents-driven interactive estimation of distribution algorithms for personalized search
L Bao, X Sun, D Gong, Y Zhang - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Personalized search is essentially a complex qualitative optimization problem, and
interactive evolutionary algorithms (EAs) have been extended from EAs to adapt to solving it …
interactive evolutionary algorithms (EAs) have been extended from EAs to adapt to solving it …
Deep learning techniques for agronomy applications
This editorial introduces the Special Issue, entitled “Deep Learning (DL) Techniques for
Agronomy Applications”, of Agronomy. Topics covered in this issue include three main …
Agronomy Applications”, of Agronomy. Topics covered in this issue include three main …
Recommendation algorithm using SVD and weight point rank (SVD-WPR)
One of the most prevalent recommendation systems is ranking-oriented collaborative
filtering which employs ranking aggregation. The collaborative filtering study recently …
filtering which employs ranking aggregation. The collaborative filtering study recently …
Addressing the New Item problem in video recommender systems by incorporation of visual features with restricted Boltzmann machines
Over the past years, the research of video recommender systems (RSs) has been mainly
focussed on the development of novel algorithms. Although beneficial, still any algorithm …
focussed on the development of novel algorithms. Although beneficial, still any algorithm …
Harnessing hybrid deep learning approach for personalized retrieval in e-learning
The current worldwide pandemic has significantly increased the need for online learning
platforms, hence presenting difficulty in choosing appropriate course materials from the vast …
platforms, hence presenting difficulty in choosing appropriate course materials from the vast …
Embedding ranking-oriented recommender system graphs
Graph-based recommender systems (GRSs) analyze the structural information available in
the graphical representation of data to make better recommendations, especially when …
the graphical representation of data to make better recommendations, especially when …