Year: 2024
Type: article
Abstract: Recommender systems are super popular nowadays for giving personalized recommendations to users. The paper focuses on a special type of recommender system aimed to advise an improvement of a user’s presentation based on slides classification. Classification is a fundamental task in information extraction and retrieval with a goal to assign given resource to a predefined class. In some cases, as in slides’ categorization, resources can belong to multiple classes, leading to a multi-labelled classification problem. Two different approaches for solving a multi-labelled image classification problem for the purpose of a presentation recommender system are suggested and evaluated in the paper. They are based on problem transformation and algorithm adaptation strategies and utilize a convolutional neural network for model training.
DOI: 10.59035/puye7368
Authors: Maria Vlahova–Takova, Milena Lazarova
Institution: Technical University of Sofia
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Funder: European Commission
OpenAlex ID: W4404963856