A New Evolving Tree-Based Model with Local Re-learning for Document Clustering and Visualization

@article{Chang2017ANE,
  title={A New Evolving Tree-Based Model with Local Re-learning for Document Clustering and Visualization},
  author={W. L. Chang and K. M. Tay and C. Lim},
  journal={Neural Processing Letters},
  year={2017},
  volume={46},
  pages={379-409}
}
  • W. L. Chang, K. M. Tay, C. Lim
  • Published 2017
  • Computer Science
  • Neural Processing Letters
  • The Evolving tree (ETree) is a hierarchical clustering and visualization model that allows the number of clusters to grow and evolve with new data samples in an online learning manner. While many hierarchical clustering models are available in the literature, ETree stands out because of its visualization capability. It is an enhancement of the Self-Organizing Map, a famous and useful clustering and visualization model. ETree organises the trained data samples in the form of a tree structure for… CONTINUE READING
    1 Citations
    Intelligent Text Clustering Based on Semantics Similarity

    References

    SHOWING 1-10 OF 61 REFERENCES
    A New Evolving Tree for Text Document Clustering and Visualization
    • 7
    • PDF
    Enhancing an Evolving Tree-based text document visualization model with Fuzzy c-Means clustering
    • 5
    • PDF
    The Evolving Tree—A Novel Self-Organizing Network for Data Analysis
    • 68
    • PDF
    Fast Growing Self Organizing Map for Text Clustering
    • 11
    The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data
    • 406
    • PDF
    Ontology-based Text Document Clustering
    • 167
    • PDF
    Mining massive document collections by the WEBSOM method
    • 190
    • Highly Influential
    • PDF
    WEBSOM - Self-organizing maps of document collections
    • 605
    • Highly Influential
    • PDF
    A Similarity Measure for Text Classification and Clustering
    • 249