Usporedba algoritama za analizu potrošačke košare

undergraduate thesis

• Title (english): Comparison of Algorithms for Basket Market Analysis
• Author: Josipa Tomić
• Mentor: Marin Šilić (mentor)
• Committee member: Marin Šilić (predsjednik povjerenstva)
• Committee member: Petar Afrić (član povjerenstva)
• Committee member: Lucija Šikić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2020-08-27, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U ovom radu opisan je proces analize potrošačke košare. Analiza potrošačke košare uobičajen je primjer pronalaska čestih podskupova velikog skupa elemenata. Pronalaženje čestih podskupova služi otkrivanju asocijativnih veza između elemenata sadržanih u velikoj relacijskoj ili transakcijskoj bazi podataka. U radu su opisani i programski ostvareni neki od najpoznatijih algoritama za pronalaženje čestih podskupova elemenata: A-Priori, FP-growth te ECLAT. Implementirani su algoritmi ispitani na velikom skupu transakcija te su prikazani rezultati izvođenja. Konačno je dana međusobna usporedba rezultata izvođenja programski ostvarenih algoritama i njihovih općih karakteristika.

Abstract (english)

In this paper, process of market basket analysis is described. Market basket analysis is a common example of mining frequent itemsets in a large data set. Mining frequent itemsets is used for discovering association relationships among elements from transactional or relational data sets. In this paper, some of the most popular algorithms for finding frequent itemsets are described and implemented, such as A-Priori, FP-growth and ECLAT. The implemented algorithms are tested on a large set of transactions and the performance results are presented. Finally, a comparison of the performance results of the implemented algorithms and their general characteristics is given.

• Keywords: analiza potrošačke košare; česti podskupovi podataka; algoritmi za pronalaženje čestih podskupova elemenata; A-Priori; FP-growth; ECLAT; veliki skup predmeta; prag potpore
• Keywords (english): Market Basket Analysis; frequent itemsets; algorithms for mining frequent itemsets; A-Priori; FP-growth; ECLAT; large data sets; support threshold
• Language: croatian
• URN:NBN: urn:nbn:hr:168:485737
• 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: 2023-01-13 14:03:05