Web Content Mining

Web Content Mining is the academic discipline within Web Mining that focuses on extracting and analyzing meaningful information, patterns, and knowledge directly from the textual, structural, and multimedia content of web pages, distinguishing it from methods concerned with web usage or link structure analysis.

1.1K

Publications

58.8K

Citations

2.5K

Authors

872

Institutions

Publications per year

2017–2026

145

Parents

Authors

2.5K

  1. JD
    Juan D. Velásquez

    University of Chile, Chile

    10 publications · 282 citations

    10

    h-index

  2. BL
    Bing Liu

    University of Illinois Chicago, United States

    8 publications · 1.3K citations

    8

    h-index

  3. JH
    Jan-Ming Ho

    Institute of Information Science, Academia Sinica, Taiwan

    7 publications · 651 citations

    7

    h-index

  4. WM
    Wei‐Ying Ma

    Microsoft Research Asia (China), China

    7 publications · 1.2K citations

    7

    h-index

  5. HK
    Hung‐Yu Kao

    National Cheng Kung University, Taiwan

    6 publications · 231 citations

    6

    h-index

1–5 of 2.5K

Venues

  1. Expert Systems with Applications

    20 publications · 1.2K citations

    16

    h-index

  2. International Journal of Computer Applications

    13 publications · 375 citations

    12

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 10 publications · 704 citations

    10

    h-index

  4. ACM SIGKDD Explorations Newsletter

    10 publications · 3K citations

    10

    h-index

  5. Scientometrics

    9 publications · 385 citations

    9

    h-index

1–5