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    This study introduces cite2vec, a novel visualization method for document collections. It enables users to explore documents based on their usage patterns, offering a new perspective beyond traditional word-based representations.

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    Area of Science:

    • Information Visualization
    • Computer Science
    • Digital Libraries

    Background:

    • Traditional document visualization focuses on content (words).
    • Effective exploration of large document collections remains a challenge.
    • User search behavior in research offers an alternative perspective for visualization.

    Purpose of the Study:

    • To develop a new visualization scheme, cite2vec, for exploring document collections based on document usage.
    • To enable dynamic exploration and comparison of documents through their citation contexts.
    • To leverage user-driven semantic concept exploration for document discovery.

    Main Methods:

    • Developed cite2vec, a usage-oriented visualization scheme.
    • Utilized a joint high-dimensional embedding space for words and documents.
    • Enabled user interaction through semantic concept prescription (phrase/document compositions and analogies).
    • Captured document usage via citation contexts.

    Main Results:

    • Demonstrated dynamic exploration and browsing of documents based on usage.
    • Showcased the ability to steer document projections using semantic concepts.
    • Validated the approach through case studies on a computer vision research paper corpus.

    Conclusions:

    • Usage-based document visualization offers a powerful alternative to content-based methods.
    • cite2vec facilitates intuitive exploration and comparison of documents by their use.
    • This approach enhances document discovery and understanding within large collections.