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Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
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Exploring Multivariate Event Sequences Using Rules, Aggregations, and Selections.

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    This study introduces Eventpad, a novel approach for analyzing complex event sequences with multiple data attributes. It enables simultaneous exploration of multivariate and sequential data, enhancing pattern discovery in real-world datasets.

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    Area of Science:

    • Computer Science
    • Data Analysis
    • Information Visualization

    Background:

    • Multivariate event sequences are common in various domains like travel, telecommunications, and server logs.
    • Existing analysis methods often focus on either temporal or structural aspects of event data, but not both simultaneously.
    • Events possess not only temporal information but also associated multivariate data, requiring integrated analysis.

    Purpose of the Study:

    • To develop an integrated approach for exploring multivariate event sequences at both multivariate and sequential levels.
    • To enable users to define and apply rewrite rules using multivariate regular expressions for pattern discovery.
    • To facilitate interactive enrichment and simplification of event sequences for deeper investigation.

    Main Methods:

    • A novel approach allowing simultaneous exploration of multivariate and sequential event data.
    • Interactive definition of rewrite rules using multivariate regular expressions.
    • A bottom-up, glyph-oriented approach (Eventpad) for searching, clustering, and aligning event sequences.
    • Storing identified patterns as new event types or attributes for further analysis.

    Main Results:

    • Demonstrated effectiveness of the approach using real-world datasets, including telecommunication traffic and hospital treatments.
    • Enabled users to simultaneously analyze temporal and multivariate attributes of event sequences.
    • Facilitated the discovery and utilization of domain-specific patterns within complex event data.

    Conclusions:

    • The proposed approach effectively addresses the limitations of existing methods for analyzing multivariate event sequences.
    • Eventpad provides a powerful tool for interactive exploration and pattern discovery in complex, real-world event data.
    • Simultaneous analysis of multivariate and sequential data enriches the understanding and simplification of event sequences.