Text Mining

Text Mining is the computational process of discovering meaningful patterns, relationships, and insights from unstructured text data by leveraging techniques from natural language processing, data mining, and computational linguistics to transform textual information into structured knowledge.

22.3K

Publications

1.4M

Citations

46.1K

Authors

6.5K

Institutions

Publications per year

2017–2026

9.3K

Authors

46.1K

  1. BL
    Bing Liu

    University of Illinois Chicago, United States

    64 publications · 27.1K citations

    48

    h-index

  2. JH
    Jiawei Han

    University of Illinois Urbana-Champaign, United States

    85 publications · 9.3K citations

    40

    h-index

  3. CZ
    ChengXiang Zhai

    University of Illinois Urbana-Champaign, United States

    52 publications · 6.2K citations

    32

    h-index

  4. CL
    C. Lee Giles

    Pennsylvania State University, United States

    54 publications · 3K citations

    29

    h-index

  5. PS
    Philip S. Yu

    University of Illinois Chicago, United States

    33 publications · 5.7K citations

    27

    h-index

1–5 of 46.1K

Venues

  1. Expert Systems with Applications

    294 publications · 25K citations

    82

    h-index

  2. IEEE Access

    344 publications · 18K citations

    69

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 165 publications · 17.1K citations

    67

    h-index

  4. Information Processing & Management

    163 publications · 22.3K citations

    61

    h-index

  5. Procedia Computer Science

    253 publications · 12.7K citations

    59

    h-index

1–5