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CNN based multi-label image classification for presentation recommender system

2024, vol.16 , no.4, pp. 73-84

Article [2024-04-07]

Authors
Maria Vlahova-Takova
Milena Lazarova
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.

Keywords

multi-labelled classification, image classification, convolutional neural network, recommender system

DOI

https://doi.org/10.59035/PUYE7368

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Citation of this article:

Maria Vlahova-Takova, Milena Lazarova. CNN based multi-label image classification for presentation recommender system. International Journal on Information Technologies and Security, vol.16 , no.4, 2024, pp. 73-84. https://doi.org/10.59035/PUYE7368