A STUDY OF N-GRAM REPRESENTATION IN HMRFKMEANS ALGORITHM FOR DOCUMENT CLUSTERING
HMRF-KMeans algorithm satisfies some requirements of document clustering, including high dimensionality data, scalability, accuracy, independent to the prior domain knowledge. The algorithm does not satisfy the requirements about meaningful cluster description and data representation that preserves...
Saved in:
Main Author: | WIDYASTUTI , HILDA |
---|---|
Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/8143 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Similar Items
-
Deep metric based feature engineering to Improve document-level representation for document clustering
by: Xu, Liwen
Published: (2022) -
Semi-supervised clustering algorithms for web documents
by: Hua, Yunke.
Published: (2013) -
Semi-supervised clustering algorithms for web documents
by: Bian, Zhiwei.
Published: (2011) -
Incremental learning of concept cluster on background net for fuzzy granulation of document representation
by: Lo, S.-L., et al.
Published: (2014) -
Evaluation of semi-supervised classification algorithms with deep contextualizes document representations
by: Yong, Hao
Published: (2021)