Sparse Document Representation

Sparse Document Representation is a document representation method in which a document is encoded using a high-dimensional vector space wherein most features are zero, thereby emphasizing a small subset of salient terms or indices to distinguish documents within a corpus.

106

Publications

6.5K

Citations

347

Authors

155

Institutions

Publications per year

2017–2026

35

Authors

347

  1. BC
    Boli Chen

    Beijing Jiaotong University, China

    3 publications · 214 citations

    3

    h-index

  2. LE
    Laurent El Ghaoui

    University of California, Berkeley, United States

    3 publications · 62 citations

    3

    h-index

  3. MP
    Min Peng

    Wuhan University, China

    3 publications · 95 citations

    3

    h-index

  4. QX
    Qianqian Xie

    University of Manchester, United Kingdom

    3 publications · 95 citations

    3

    h-index

  5. LJ
    Liping Jing

    Beijing Jiaotong University, China

    3 publications · 214 citations

    3

    h-index

1–5 of 347

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 195 citations

    5

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 146 citations

    3

    h-index

  3. Mathematical Problems in Engineering

    MPE · 2 publications · 35 citations

    2

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 2 publications · 81 citations

    2

    h-index

  5. Information Sciences

    2 publications · 60 citations

    2

    h-index

1–5