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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Published on: August 14, 2018

On Constructing Seminal Paper Genealogy.

Duck-Ho Bae, Se-Mi Hwang, Sang-Wook Kim

    IEEE Transactions on Cybernetics
    |June 13, 2013
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces algorithms to identify seminal papers and trace their influence. It helps researchers understand a topic's foundational literature and its evolution.

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    Area of Science:

    • Bibliometrics
    • Information Science
    • Computer Science

    Background:

    • Researchers often face challenges identifying foundational papers in new research areas.
    • Understanding the genealogy of seminal works is crucial for grasping a topic's historical development.

    Purpose of the Study:

    • To develop algorithms for identifying seminal papers within a given research topic.
    • To propose methods for measuring the influence between academic papers.
    • To construct the genealogy of seminal papers using influence and citation data.

    Main Methods:

    • An algorithm is proposed to identify a set of seminal papers on a specific topic.
    • Influence measures are defined to quantify the impact of one paper on another.
    • A second algorithm constructs paper genealogies based on influence and citation networks.

    Main Results:

    • The study addresses performance and scalability concerns of the proposed algorithms.
    • Extensive experiments on real-world academic literature demonstrate the effectiveness and efficiency of the approach.
    • The developed methods successfully identify seminal papers and map their historical influence.

    Conclusions:

    • The proposed algorithms provide a robust solution for identifying seminal papers and their influence.
    • This work aids researchers in navigating complex academic landscapes and understanding research lineage.
    • The findings contribute to bibliometric analysis and the study of scientific knowledge evolution.