Detekcija korisničkih interakcija u svrhu stvarno-vremenske procjene iskustvene kvalitete usluge YouTube temeljena na strojnom učenju

master's thesis

• Title (english): Machine Learning-Based User Interaction Detection for Real-time YouTube Quality of Experience Estimation
• Author: Filip Matić
• Mentor: Lea Skorin-Kapov (mentor)
• Committee member: Lea Skorin-Kapov (predsjednik povjerenstva)
• Committee member: Mirko Sužnjević (član povjerenstva)
• Committee member: Maja Matijašević (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2020-07-07, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U posljednje vrijeme na globalnoj razini bilježimo sve veći porast broja korisnika Interneta. To dovodi i do sve većeg porasta u globalnom Internet prometu. Upravo sve učestalije korištenje usluga video strujanja pridonosi tom porastu. Budući da je većina Internet prometa kriptirana to predstavlja problem davateljima mrežnih usluga pri praćenju iskustvene kvalitete usluge krajnjim korisnicima. Dodatno, korisničke interakcije koje su u vezi s prikazivanjem video sadržaja utječu na uzorke u mrežnom prometu i otežavaju procjenu iskustvene kvalitete. U sklopu ovog rada se pomoću tehnika strojnog učenja ispituje mogućnost otkrivanja korisničkih interakcija u stvarnom vremenu.

Abstract (english)

Nowadays, on the global scale there is an ever-increasing number of Internet users. This has led to a rise in global Internet traffic, driven mostly by increased usage of video streaming services. The fact that most of the Internet traffic is encrypted poses a problem for ISPs to monitor and meet end user Quality of Experience (QoE) expectations. Furthermore, user interactions during video playback have an impact on network traffic patterns and make the assessment of QoE more difficult. This thesis analyses solutions that employ machine learning techniques to detect user interactions in real time.

• Keywords: korisničke interakcije; iskustvena kvaliteta; strojno učenje; YouTube
• Keywords (english): user interactions; Quality of Experience; Machine learning; YouTube
• Language: croatian
• URN:NBN: urn:nbn:hr:168:421038
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-13 13:04:29