Text summarization using latent semantic analysis

Date

2011

Author

Özsoy, Makbule Gülçin

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Text summarization solves the problem of presenting the information needed by a user in a compact form. There are different approaches to create well formed summaries in literature. One of the newest methods in text summarization is the Latent Semantic Analysis (LSA) method. In this thesis, different LSA based summarization algorithms are explained and two new LSA based summarization algorithms are proposed. The algorithms are evaluated on Turkish and English documents, and their performances are compared using their ROUGE scores.

Subject Keywords

Semantics

URI

http://etd.lib.metu.edu.tr/upload/12612988/index.pdf
https://hdl.handle.net/11511/20354

Collections

Graduate School of Natural and Applied Sciences, Thesis