Primjena binarne klasifikacije na problem pronalaska najboljih prijatelja na društvenoj mreži

master's thesis

• Title (english): Applying the binary classification methods for discovering the best friends on an online social network
• Author: Maja Stupalo
• Mentor: Zoran Skočir (mentor)
• Committee member: Zoran Skočir (predsjednik povjerenstva)
• Committee member: Boris Vrdoljak (član povjerenstva)
• Committee member: Damir Pintar (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2016-07-08, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Electrical Engineering

Abstract

Društvene mreže su jedan od najpopularnijih usluga temeljenih na internetskoj infrastrukturi, dok je Facebook najpopularnija društvena mreža. U ovome radu pokušava se binarnom klasifikacijom podijeliti prijateljstva na Facebooku u one koji su bliski prijatelji i one koji nisu, promatrajući njihove parametre komunikacije. Ispituje se uspješnost predviđanja algoritama nadziranog učenja, nad podacima dobivenim s društvene mreže, kako bi se predvidjelo jesu li prijatelji bliski ili ne.

Abstract (english)

Social networks are one of the most popular services based on the Internet infrastructure, while Facebook is the most popular social network. Using binary classification, this paper attempts to divide friendships on Facebook on those who are close friends and those who are not, i.e. finding the best friends by watching their communication parameters. The performance of the prediction algorithms with supervised learning was examined using data obtained from the social networks, in order to... More predict whether observed users are close friends or not. Less

• Keywords: Društvene mreže; binarna klasifikacija; Facebook; nadzirano učenje; algoritmi
• Keywords (english): Social Networks; Binary Classification; Facebook; Supervised Learning; Algorithms
• Language: croatian
• URN:NBN: urn:nbn:hr:168:141853
• Study programme: Title: Information and Communication Technology; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka informacijske i komunikacijske tehnologije (magistar/magistra inženjer/inženjerka informacijske i komunikacijske tehnologije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2018-02-06 12:08:53