ePrints.FRI - University of Ljubljana, Faculty of Computer and Information Science

Predicting the click-through rate of ads using factorization machines

Robert Dovžan (2019) Predicting the click-through rate of ads using factorization machines. EngD thesis.

Download (1703Kb)


    In the field of programmatic advetising based on the ecosystem called realtime bidding, it is important to know, how successful an ad impression will be. Click-through rate prediction is one of the biggest challenges in online advertising. In this thesis we use factorization machines to predict the clickthrough rate based on data about the ad, website, user etc. We describe the process of data preparation, feature selection, implementation and testing. The goal is to improve the current solution in company Zemanta d.o.o. which is based on logistic regression. With local testing and online A/B testing we reach our goal and contribute to improving the service and financial performance of the company

    Item Type: Thesis (EngD thesis)
    Keywords: factorization machines, advertising, ads, prediction, machine learning, data mining
    Number of Pages: 56
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Lovro ŠubeljMentor
    Davorin KopičComentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1538205891)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 4416
    Date Deposited: 26 Mar 2019 11:54
    Last Modified: 16 Apr 2019 12:37
    URI: http://eprints.fri.uni-lj.si/id/eprint/4416

    Actions (login required)

    View Item