A review on deep learning for recommender systems: challenges and remedies
Recommender systems are effective tools of information filtering that are prevalent due to
increasing access to the Internet, personalization trends, and changing habits of computer …
increasing access to the Internet, personalization trends, and changing habits of computer …
A brief survey of machine learning and deep learning techniques for e-commerce research
The rapid growth of e-commerce has significantly increased the demand for advanced
techniques to address specific tasks in the e-commerce field. In this paper, we present a …
techniques to address specific tasks in the e-commerce field. In this paper, we present a …
[HTML][HTML] Deep learning based semantic personalized recommendation system
The past decade has seen significant development in the number of personalized
recommendation applications on the World Wide Web. It aims to assist users to retrieve …
recommendation applications on the World Wide Web. It aims to assist users to retrieve …
Learning attribute representations with localization for flexible fashion search
In this paper, we investigate ways of conducting a detailed fashion search using query
images and attributes. A credible fashion search platform should be able to (1) find images …
images and attributes. A credible fashion search platform should be able to (1) find images …
[HTML][HTML] Vector database management systems: Fundamental concepts, use-cases, and current challenges
T Taipalus - Cognitive Systems Research, 2024 - Elsevier
Vector database management systems have emerged as an important component in
modern data management, driven by the growing importance for the need to …
modern data management, driven by the growing importance for the need to …
Leveraging weakly annotated data for fashion image retrieval and label prediction
C Corbiere, H Ben-Younes… - Proceedings of the …, 2017 - openaccess.thecvf.com
In this paper, we present a method to learn a visual representation adapted for e-commerce
products. Based on weakly supervised learning, our model learns from noisy datasets …
products. Based on weakly supervised learning, our model learns from noisy datasets …
SoK: Exploring the state of the art and the future potential of artificial intelligence in digital forensic investigation
X Du, C Hargreaves, J Sheppard, F Anda… - Proceedings of the 15th …, 2020 - dl.acm.org
Multi-year digital forensic backlogs have become commonplace in law enforcement
agencies throughout the globe. Digital forensic investigators are overloaded with the volume …
agencies throughout the globe. Digital forensic investigators are overloaded with the volume …
Image-based fashion product recommendation with deep learning
We develop a two-stage deep learning framework that recommends fashion images based
on other input images of similar style. For that purpose, a neural network classifier is used as …
on other input images of similar style. For that purpose, a neural network classifier is used as …
Content-based artwork recommendation: integrating painting metadata with neural and manually-engineered visual features
Recommender Systems help us deal with information overload by suggesting relevant items
based on our personal preferences. Although there is a large body of research in areas such …
based on our personal preferences. Although there is a large body of research in areas such …
Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond
Visual similarities discovery (VSD) is an important task with broad e-commerce applications.
Given an image of a certain object, the goal of VSD is to retrieve images of different objects …
Given an image of a certain object, the goal of VSD is to retrieve images of different objects …