- Copyright:
- 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, 1002; 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).
- Links To Paper
- 1st link
- Bibtex format
- @InProceedings{EDI-INF-RR-1184,
- author = {
Freddy Y.Y. Choi
and Peter Wiemer-Hastings
and Johanna Moore
},
- title = {Latent Semantic Analysis for Text Segmentation},
- book title = {Proceedings of Empirical Methods in Natural Language Processing (EMNLP)},
- year = 2001,
- month = {Jun},
- url = {http://www.cs.cornell.edu/home/llee/emnlp/papers/choi.pdf},
- }
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