Bisecting k-Means Clustering Algorithm

A Bisecting k-Means Clustering Algorithm is a Divisive Clustering Algorithm that ...

• Context:
  • Requires [math]\displaystyle{ k }[/math] as input.
• See: k-Means Clustering Algorithm.

---

---

References

2003

• (Hotho et al., 2003) ⇒ Andreas Hotho, Steffen Staab, and Gerd Stumme. (2003). “Wordnet Improves Text Document Clustering.” In: Proceedings of the SIGIR Workshop on Semantic Web Workshop.

2002

• (Beil et al., 2002) ⇒ Florian Beil, Martin Ester, and Xiaowei Xu. (2002). “Frequent Term-based Text Clustering.” In: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2002). doi:10.1145/775047.775110
  • QUOTE: A lot of different text clustering algorithms have been proposed in the literature, including Scatter/Gather (Cutting et al., 2002), SuffixTree Clustering (Zamir & Etzioni, 1998) and bisecting k-means (Steinbach et al.,2000). A recent comparison (Steinbach et al.,2000) demonstrates that bisecting k-means outperforms the other well-known techniques, in particular hierarchical clustering algorithms, with respect to clustering quality.

2000

• (Steinbach & al. 2000) ⇒ M. Steinbach, G. Karypis, and V. Kumar. (2000). “A Comparison of Document Clustering Techniques.” In: ProceedingsText-Mining Workshop, KDD 2000,

---