Topology-based clusterwise regression for user segmentation and demand forecasting

Rodrigo Rivera-Castro, Aleksandr Pletnev, Polina Pilyugina, Grecia Diaz, Ivan Nazarov, Wanyi Zhu, Evgeny Burnaev

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Citation (Scopus)

    Abstract

    Topological Data Analysis (TDA) is a recent approach to analyze data sets from the perspective of their topological structure. Its use for time series data has been limited. In this work, a system developed for a leading provider of cloud computing combining both user segmentation and demand forecasting is presented. It consists of a TDA-based clustering method for time series inspired by a popular managerial framework for customer segmentation and extended to the case of clusterwise regression using matrix factorization methods to forecast demand. Increasing customer loyalty and producing accurate forecasts remain active topics of discussion both for researchers and managers. Using a public and a novel proprietary data set of commercial data, this research shows that the proposed system enables analysts to both cluster their user base and plan demand at a granular level with significantly higher accuracy than a state of the art baseline. This work thus seeks to introduce TDA-based clustering of time series and clusterwise regression with matrix factorization methods as viable tools for the practitioner.

    Original languageEnglish
    Title of host publicationProceedings - 2019 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019
    EditorsLisa Singh, Richard De Veaux, George Karypis, Francesco Bonchi, Jennifer Hill
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages326-336
    Number of pages11
    ISBN (Electronic)9781728144931
    DOIs
    Publication statusPublished - Oct 2019
    Event6th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019 - Washington, United States
    Duration: 5 Oct 20198 Oct 2019

    Publication series

    NameProceedings - 2019 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019

    Conference

    Conference6th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019
    Country/TerritoryUnited States
    CityWashington
    Period5/10/198/10/19

    Keywords

    • Clusterwise
    • Demand Forecasting
    • Time Series Clustering
    • Topological Data Analysis

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