Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6905412 | Applied Soft Computing | 2015 | 10 Pages |
Abstract
- This paper presents a novel down-top incremental conceptual hierarchical text clustering approach using CFu-tree (ICHTC-CF) representation.
- For summarizing a cluster, we use the term-based feature extraction in text clustering.
- A new measure criterion, Comparison Variation (CV), is presented for judging whether the clusters can be merged or split.
- The incremental clustering method is not sensitive to the input data order.
- Experimental results show that the performance of our method outperforms k-means, which indicate our new technique is efficient and feasible.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Tao Peng, Lu Liu,