Recommender system for personalized assortment in a clothing store

Karmen Gostiša (2017) Recommender system for personalized assortment in a clothing store. EngD thesis.

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Abstract

In the diploma thesis we are dealing with the problem of developing a recommender system for a clothing store based on transaction data. We start with theoretical basics about recommenders and association rules. Afterwards we describe data and represent its quantitative and qualitative aspects. We continue with the detailed explanation of implemented methods, namely, nearest neighbors and matrix factorization. In the end we compare the results of our methods with naive method of recommending most popular products, achieving much better results. Matrix factorization produced the best results and we would use it in production.

Item Type:

Thesis (EngD thesis)

Keywords:

recommender system, content-based filtering, collaborative filtering, machine learning, matrix factorization, association rules

Number of Pages:

Language of Content:

Slovenian

Mentor / Comentors:

Name and Surname	ID	Function
izr. prof. dr. Matjaž Kukar	267	Mentor

Link to COBISS:

http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1537553347)

Institution:

University of Ljubljana

Department:

Faculty of Computer and Information Science

Item ID:

3951

Date Deposited:

14 Sep 2017 17:41

Last Modified:

29 Sep 2017 10:35

URI:

http://eprints.fri.uni-lj.si/id/eprint/3951

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