Latent Semantic Analysis for Text Segmentation
Freddy Y. Y. Choi, Peter Hastings, Johanna D. Moore · 2001
This paper describes a method for linear text segmentation that is more accurate or at least as accurate as state-of-the-art methods (Utiyama and Isahara, 2001; Choi, 2000a). Inter-sentence similarity is estimated by latent semantic analysis (LSA). Boundary locations are discovered by divisive clustering. Test results show LSA is a more accurate similarity measure than the cosine metric (van Rijsbergen, 1979).