Analiza potrošačke košarice korištenjem algoritma FP-Growth

undergraduate thesis

• Title (english): Market Basket Analysis Using FP-Growth Algorithm
• Author: Borna Popović
• Mentor: Alan Jović (mentor)
• Committee member: Alan Jović (predsjednik povjerenstva)
• Committee member: Nikolina Frid (član povjerenstva)
• Committee member: Igor Stančin (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2020-07-03, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Ovaj rad obrađuje dubinsku analizu podataka, tj. analizu potrošačke košarice uporabom algoritma FP-Growth te generiranje jednostavnih asocijativnih pravila. Potrošačka košarica sastoji od skupa transakcija koje se predaju algoritmu FP-Growth. Na temelju tog skupa transakcija algoritam uz zadani minimalni prag podrške (eng. minimal support) generira najčešće podskupove, tj. česte obrasce. Pomoću dobivenih čestih obrazaca i uz zadanu minimalnu povjerljivost, (eng. minimal confidence) generiraju se stroga asocijativna pravila. U ovom radu detaljno je objašnjen taj cijeli postupak te je nakon toga demonstrirana njegova primjena na konkretnim primjerima kako bi se pokazalo da su dobiveni rezultati jako korisni, zbog čega ih velike kompanije često koriste i analiziraju kako bi unaprijedili svoje poslovanje.

Abstract (english)

This paper processes data mining, i.e. market basket analysis using FP-Growth algorithm for frequent patterns mining and generating simple association rules. Market basket contains a set of transactions that are submitted to the algorithm. Based on the given set of transactions and minimum support count algorithm generates frequent itemsets, i.e. frequent patterns. With these frequent patterns and given minimum confidence value we can generate strict association rules. In this paper, the entire procedure is explained in detail and its use is demonstrated on a concrete example. The results obtained by analysis are very useful and are often used by large companies to improve their business.

• Keywords: dubinska analiza podataka; analiza potrošačke košarice; skup transakcija; podatak; kupac; trgovac; artikl; FP-Growth algoritam; FP-stablo; čvor; obrasci; česti podskupovi; prefiksni putevi; podskup; problem; podproblem; sufiks; minimalni prag podrške; ažuriranje; uvjetno FP-stablo; asocijativna pravila; nepovezani skupovi; podrška; formula; vjerojatnost; implementacija; razred; lista; korijen; obrađivanje; eksperimentalno vrednovanje; podstablo; rječnik; sortiranje
• Keywords (english): data mining; market basket analysis; set of transactions; data; buyer; merchant; item; FP-Growth algorithm; FP-tree; node; patterns; frequent subsets; prefix paths; subset; problem; subproblem; suffix; minimal support count; update; conditional FP-tree; association rules; disjoint itemsets; support; confidence; formula; probability; implementation; class; list; root; processing; experimental evaluation; subtree; dictionary; sorting
• Language: croatian
• URN:NBN: urn:nbn:hr:168:255320
• 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: 2022-12-28 09:12:06