Αλγόριθμοι μηχανικής μάθησης στην ανάλυση και πρόβλεψη συμπεριφοράς χρηστών στο διαδίκτυο
Machine learning algorithms for analysing and predicting user behavior on the internet
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Keywords
Αλγόριθμοι μηχανικής μάθησης ; Ανάλυση συμπεριφοράς χρηστών ; Πρόβλεψη συμπεριφοράς χρηστών ; Συστήματα συστάσεων ; Ανάλυση δεδομένωνAbstract
This thesis is about applying machine learning algorithms for the purpose of analyzing
and forecasting user activities on the Internet. It aims at the acquisition, management,
and evaluation of the user data with the goal of identifying their online tendencies and
enhancing their interaction with the digital platform. The growing usage of online
services has resulted in the production of large amounts of data, the analysis of which
is critical in identifying users’ needs and behaviors, with the aim of enhancing their
experience. This study focuses on machine learning algorithms for this purpose and
describes various prediction models and assesses their strengths and weaknesses,
while also focusing on specific aspects of supervised, unsupervised and reinforcement
learning algorithms. The findings indicate that the application of machine learning
techniques can enhance the personalization of content and user interaction and thus
contribute to the improvement of business strategies and the creation of personalized
experiences; however, there are several drawbacks that need to be addressed to
achieve the best and ethical effectiveness.
Department
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα ΠληροφορικήςNumber of pages
65Language
GreekCollections
Except where otherwise noted, this item's license is described as
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα