DocumentCode
2608214
Title
Web document retrieval using manifold learning and ACO algorithm
Author
Ziqiang, Wang ; Xia, Sun
Author_Institution
Sch. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China
fYear
2009
fDate
18-20 Oct. 2009
Firstpage
152
Lastpage
155
Abstract
To efficiently deal with high dimensionality and precision problems in document retrieval, a novel document retrieval algorithm based on manifold learning and ant colony optimization(ACO) algorithm is proposed. The high-dimensional document data are first projected into lower-dimensional feature space with neighborhood preserving embedding (NPE) algorithm, the ACO algorithm is then applied to retrieve relevant documents in the reduced lower-dimensionality document feature space. Extensive experiments on real-world data set demonstrate the effectiveness of the proposed algorithm.
Keywords
Internet; document handling; information retrieval; learning (artificial intelligence); optimisation; ACO algorithm; NPE algorithm; Web document retrieval algorithm; ant colony optimization; high-dimensional document data; lower-dimensional feature space; manifold learning; neighborhood preserving embedding; Ant colony optimization; Feedback; Information retrieval; Large scale integration; Linear discriminant analysis; Manifolds; Pattern recognition; Scattering; Space technology; Sun; Document retrieval; ant colony optimization(ACO); manifold learning; neighborhood preserving embedding(NPE);
fLanguage
English
Publisher
ieee
Conference_Titel
Broadband Network & Multimedia Technology, 2009. IC-BNMT '09. 2nd IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-4590-5
Electronic_ISBN
978-1-4244-4591-2
Type
conf
DOI
10.1109/ICBNMT.2009.5348468
Filename
5348468
Link To Document