DocumentCode :
2991406
Title :
Optimal VSM Model and Multi-Object Quantum-Inspired Genetic Algorithm for Web Information Retrieval
Author :
Yan, Lili ; Chen, Henian ; Ji, Wentian ; Lu, Yu ; Li, Junqing
Author_Institution :
Dept. of Software Eng., Hainan Software Profession Inst., Qionghai, China
fYear :
2009
fDate :
18-20 Jan. 2009
Firstpage :
1
Lastpage :
4
Abstract :
It is becoming an important research issue to search the Web rapidly and effectively from a mass of information. Information retrieval for resolved these problems provide a chance. In this paper, a new adaptive method of information retrieval Web documents is proposed. We give an algorithm QIGA which combines genetic algorithm and quantum computing based on vector space model (VSM). This algorithm avoids the disadvantage of Web documents by using pure genetic algorithm which can not be utilized accurately. Experimental results show that our method can be adopted effectively in practice and is superior to other algorithms.
Keywords :
Internet; genetic algorithms; information retrieval; quantum computing; QIGA; Web documents; Web information retrieval; multiobject quantum-inspired genetic algorithm; optimal VSM model; quantum computing; vector space model; Genetic algorithms; Indexing; Information analysis; Information retrieval; Optical computing; Quantum computing; Scalability; Search engines; Software engineering; Web sites;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Network and Multimedia Technology, 2009. CNMT 2009. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5272-9
Type :
conf
DOI :
10.1109/CNMT.2009.5374788
Filename :
5374788
Link To Document :
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