A Text Extraction and Machine Learning based-solution for Multimedia Filtering and Classification

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dc.contributor.authorBENZAOUI, Ismail
dc.contributor.authorBENZAOUI, Aya
dc.contributor.authorSupervisor :Mahmoud, BRAHIMI
dc.date.accessioned2023-07-06T09:07:10Z
dc.date.available2023-07-06T09:07:10Z
dc.date.issued2023-06-10
dc.description.abstractThe objective of this work is to propose a filter and classifier for controlling multimedia content that may be inappropriate. The filter and classifier operate by extracting text from multimedia content and subsequently classifying it using a Naive-Bayes model trained on multiple datasets. The implementation was carried out using the Python environment due to its extensive collection of machine learning-oriented libraries.en_US
dc.identifier.urihttp://dspace.univ-msila.dz:8080//xmlui/handle/123456789/40052
dc.language.isoenen_US
dc.publisherUniversity of M'silaen_US
dc.subjectMultimedia Filtering, Multimedia classification, Machine learning, Text extraction Naïve-Bayes, Python.en_US
dc.titleA Text Extraction and Machine Learning based-solution for Multimedia Filtering and Classificationen_US
dc.typeThesisen_US

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