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