Korbicz, Józef - red. ; Uciński, Dariusz - red.
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.
Zielona Góra: Uniwersytet Zielonogórski
AMCS, volume 16, number 4 (2006) ; kliknij tutaj, żeby przejść
Biblioteka Uniwersytetu Zielonogórskiego
2021-09-07
2020-08-26
102
https://www.zbc.uz.zgora.pl/publication/64120
Nazwa wydania | Data |
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Latent semantic indexing using eigenvalue analysis for efficient information retrieval | 2021-09-07 |
Moldovan, Andreea Bot, Radu Ioan Wanka, Gert Beliczyński, Bartłomiej - red.
Simek, Krzysztof Kimmel, Marek - red. Lachowicz, Mirosław - red. Świerniak, Andrzej - red.
Hofuku, Ichiro Oshima, Kunio Korbicz, Józef - red. Uciński, Dariusz - red.
Aswani Kumar, Cherukuri Korbicz, Józef - red. Uciński, Dariusz - red.
Kocsor, András Dombi, József Bálint, Imre Korbicz, Józef - red. Uciński, Dariusz - red.
Singh, Prem Kumar Aswani Kumar, Cherukuri Gani, Abdullah Korbicz, Józef - red. Uciński, Dariusz - red.
Izyan, Nurul Mat Daud Sabri, Nur Ain Ayunni Hafizah, A. K. Nor Sankar, D.S. Viswanathan, K.K. Jurczak, Paweł - red.
Medisetty, Padma Devi Suripeddi, Srinivas Badeti, Satyanarayana Kuppalapalle, Vajravelu Jurczak, Paweł - red.