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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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    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: 56
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    izr. prof. dr. Matjaž Kukar267Mentor
    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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