- Tytuł:
- Latent semantic indexing using eigenvalue analysis for efficient information retrieval
- Autorzy:
-
Aswani Kumar, Ch.
Srinivas, S. - Powiązania:
- https://bibliotekanauki.pl/articles/908375.pdf
- Data publikacji:
- 2006
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
wyszukiwanie informacji
indeksowanie semantyczne
wartość własna
wektor przestrzenny
information retrieval
latent semantic indexing
eigenvalues
rank reduction
singular value decomdecomposition
vector space method - Opis:
- Text retrieval using Latent Semantic Indexing (LSI) with truncated Singular Value Decomposition (SVD) has been intensively studied in recent years. However, the expensive complexity involved in computing truncated SVD constitutes a major drawback of the LSI method. In this paper, we demonstrate how matrix rank approximation can influence the effectiveness of information retrieval systems. Besides, we present an implementation of the LSI method based on an eigenvalue analysis for rank approximation without computing truncated SVD, along with its computational details. Significant improvements in computational time while maintaining retrieval accuracy are observed over the tested document collections.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2006, 16, 4; 551-558
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł