Text summarization using Latent Semantic Analysis

Creative Commons License

Ozsoy M. G., Alpaslan F. N., Çiçekli İ.

JOURNAL OF INFORMATION SCIENCE, cilt.37, ss.405-417, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 37
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1177/0165551511408848
  • Dergi Adı: JOURNAL OF INFORMATION SCIENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.405-417
  • Anahtar Kelimeler: information retrieval, Latent Semantic Analysis, text summarization
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Text summarization solves the problem of presenting the information needed by a user in a compact form. There are different approaches to creating well-formed summaries. One of the newest methods is the Latent Semantic Analysis (LSA). In this paper, different LSA-based summarization algorithms are explained, two of which are proposed by the authors of this paper. The algorithms are evaluated on Turkish and English documents, and their performances are compared using their ROUGE scores. One of our algorithms produces the best scores and both algorithms perform equally well on Turkish and English document sets.