Central Idea Detection

Central Idea Detection is a scholarly methodology within the field of text analysis that identifies the primary conceptual contribution of a research paper by distinguishing its core intellectual innovation from ancillary or supporting elements.

3

Publications

87

Citations

11

Authors

6

Institutions

Publications per year

2017–2026

3

Authors

11

  1. SB
    Sameer B. Srivastava

    University of California, Berkeley, United States

    1 publications · 19 citations

    1

    h-index

  2. RA
    Reima Al-Jarf

    King Saud University, Saudi Arabia

    1 publications · 20 citations

    1

    h-index

  3. CC
    Chih‐Cheng Chen

    Jimei University, China

    1 publications · 48 citations

    1

    h-index

  4. FG
    Fang Gao

    Jilin University, China

    1 publications · 48 citations

    1

    h-index

  5. ZZ
    Zhiyun Zhao

    Institute of Scientific and Technical Information of China, China

    1 publications · 48 citations

    1

    h-index

1–5 of 11

Venues

  1. Microsystem Technologies

    1 publications · 48 citations

    1

    h-index

  2. SSRN Electronic Journal

    Repository · 1 publications · 20 citations

    1

    h-index

  3. PNAS Nexus

    1 publications · 19 citations

    1

    h-index

1–3