1. Αρχική σελίδα
  2. Αναζήτηση

Web content classification analysis

Το τεκμήριο παρέχεται από τον φορέα :
International Hellenic University   

Αποθετήριο :
Institutional Repository of the International Hellenic University   

δείτε την πρωτότυπη σελίδα τεκμηρίου
στον ιστότοπο του αποθετηρίου του φορέα για περισσότερες πληροφορίες και για να δείτε όλα τα ψηφιακά αρχεία του τεκμηρίου*



Web content classification analysis (EN)
Nissopoulou, Theopisti Xeni (EN)
Karapiperis, Dimitrios (EL)
Diamantaras, Konstantinos (EN)
masterThesis
2023-04-11T12:09:35Z
2023-04-11
2023-01-07
This dissertation was written as a part of the MSc in Data Science at the International Hellenic University. Web analytics is a way for companies to learn more about the people who visit their websites. This information may include things like how people use the pages on a site, and how they respond to different types of content. These types of analytics can help to determine future decisions regarding the content and marketing which may help on how the company is perceived from the customers, as well as it can even improve their status and the profit. In order to gain valuable insights from a series of site visits and other related interaction data, it is essential to have accurate data. In the current work, Web Content Text Classification is to be done over the extracted content of a company’s portal by categorizing those into 19 brands. Natural Language Processing techniques and Machine Learning algorithms have been applied and described. After evaluating the results of the models, it was concluded that BERT, which is a powerful deep learning model, and in particular Bert Base Uncased, performed the best, making accurate predictions and having good performance overall. (EL)
Classification analysis (EL)
Web content (EN)
Αγγλική γλώσσα
School of Science and Technology, MSc in Data Science
IHU (EL)
Default License
International Hellenic University
Institutional Repository of the International Hellenic University
University Center of International Programmes of Studies (UCIPS)
Master Theses



*Η εύρυθμη και αδιάλειπτη λειτουργία των διαδικτυακών διευθύνσεων των συλλογών (ψηφιακό αρχείο, καρτέλα τεκμηρίου στο αποθετήριο) είναι αποκλειστική ευθύνη των αντίστοιχων Φορέων περιεχομένου.