|
|
Natural Language Retrieval for Latent Semantic Indexing |
Tao Yuehua1 Sun Maosong2 |
1(Department of Computer Science, Yunnan Normal University, Kunming 650031, China)
2(Department of Computer Science and Technology; Tsinghua University, Beijing 10084, China) |
|
|
Abstract In information retrieval, vector space model is one of significant mathematics tools. Because of the speciality of natural language retrieval (NLR) and the affection of synonym and polysemy in tradition information retrieval model, the precision of retrieval is not high. In order to imporve the precision of NLR, the authors discuss information retrieval model based on concept--Latent Semantic Indexing (LSI), and analysis two examples of LSI.
|
Received: 30 December 2000
Published: 25 October 2001
|
|
Corresponding Authors:
Tao Yuehua,Sun Maosong
|
About author:: Tao Yuehua,Sun Maosong |
[1]Jennifer Chu-Carroll&Bob Carpenter.1999.Vector-based Natural Language Call Routing.Computational Linguistics,25
(3):361-388
[2]Michael W.Berry and Murray Browne.Understanding Search Engines Mathematical Modeling and Text Retrieval.University
of Tennessee.USA
[3]Deer wester,Scott,Susan T.Dumais,George W.Furnas,Thomas K.Landauer,and Richard Harshman.1990.Indexing
by Latent Semantic Analysis.Journal of the American Society for Information Science,41(6):391-407.
[4]刘博勤,丁晓明.潜语义标引与汉语信息检索研究.计算机科学,2000,27(3):93-95
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|