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Interactive Event Sequence Prediction for Marketing Analysts

Published: 25 April 2020 Publication History

Abstract

Timestamped event sequences are analyzed to tackle varied problems but have unique challenges in interpretation and analysis. Especially in event sequence prediction, it is difficult to convey the results due to the added uncertainty and complexity introduced by predictive models. In this work, we design and develop ProFlow, a visual analytics system for supporting analysts' workflow of exploring and predicting event sequences. Through an evaluation conducted with four data analysts in a real-world marketing scenario, we discuss the applicability and usefulness of ProFlow as well as its limitations and future directions.

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Cited By

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  • (2022)Survey on Visual Analysis of Event Sequence DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.310041328:12(5091-5112)Online publication date: 1-Dec-2022
  • (2022)A Data-Centric Methodology and Task Typology for Time-Stamped Event Sequences2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)10.1109/BELIV57783.2022.00012(66-76)Online publication date: Oct-2022
  • (2021)Efficient Methods for Clickstream Pattern Mining on Incremental DatabasesIEEE Access10.1109/ACCESS.2021.31315779(161305-161317)Online publication date: 2021

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  1. Interactive Event Sequence Prediction for Marketing Analysts

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    cover image ACM Conferences
    CHI EA '20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
    April 2020
    4474 pages
    ISBN:9781450368193
    DOI:10.1145/3334480
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Published: 25 April 2020

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    Author Tags

    1. event sequence analysis
    2. predictive analytics
    3. visualization

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    View all
    • (2022)Survey on Visual Analysis of Event Sequence DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.310041328:12(5091-5112)Online publication date: 1-Dec-2022
    • (2022)A Data-Centric Methodology and Task Typology for Time-Stamped Event Sequences2022 IEEE Evaluation and Beyond - Methodological Approaches for Visualization (BELIV)10.1109/BELIV57783.2022.00012(66-76)Online publication date: Oct-2022
    • (2021)Efficient Methods for Clickstream Pattern Mining on Incremental DatabasesIEEE Access10.1109/ACCESS.2021.31315779(161305-161317)Online publication date: 2021

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