Sustav preporučivanja na temelju zapisa prijašnjih korisničkih odabira

undergraduate thesis

• Title (english): Recommendation System Based on Records of Previous User Activities
• Author: Patrik Marić
• Mentor: Klemo Vladimir (mentor)
• Committee member: Klemo Vladimir (predsjednik povjerenstva)
• Committee member: Goran Delač (član povjerenstva)
• Committee member: Marin Šilić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2018-07-13, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U radu su ukratko opisani općenito sustavi preporuke, s naglaskom na suradničko filtriranje. Opisane su neke od metodi računanja sličnosti između korisnika, te nakon toga pristupi ka odabiru susjedstva i za kraj pristupi izračunu procijenjenih ocjena koje bi određeni korisnik dao artiklima koje nije ocijenio.
Nakon općenitog opisa sustava preporuke, ukratko su opisane implementacije sustava implementiranih u sklopu ovoga rada. Te nakon toga je provedena i usporedba, odnosno vrednovanje istih. Sustavi su uspoređeni po susjedstvima koje pronalaze, te po pronađenim preporukama, te na kraju i vremenu izvođenja.

Abstract (english)

In the beginning of this paper is a brief description of recommender systems in general, with focus on collaborative filtering. Further on, there are described some of the similarity measures and some of the approaches to defining the neighbourhood of a user, lastly there are described few ways of estimating a grade for an item that hasn’t been graded by the user.
After the brief description of recommender systems in general, implementations of the recommender systems implemented within this paper’s thesis were described. In the end the implemented systems were evaluated and compared. Systems were compared by the found neighborhood for a user, grades estimated, and finally execution times.

• Keywords: Sustav preporuke; suradničko filtriranje; Neo4j
• Keywords (english): Recommender system; collaborative filtering; Neo4j
• Language: croatian
• URN:NBN: urn:nbn:hr:168:008457
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2019-03-13 22:39:29