A novel incremental conceptual hierarchical text clustering method using CFu-tree

- 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.