%0 Journal Article
%T Web search model and optimal algorithm based on mean quantity of Web pages<br>基于Web页面平均质量的Web搜索模型和优化算法
%A FU Guo-yu
%A HUANG Xian-ying
%A <br>付国瑜
%A 黄贤英
%J 计算机应用
%D 2009
%I 
%X This paper proposed a search strategy based on Quantum Genetic Clonal Mining Algorithm (QGCMA) for Web search. The user query was used to mathematically define a mean quantity of Web pages, and evolved a population of Web pages for maximizing the affinity by clonal, mutation and crossover operator. The analysis and experimental results show that the proposed method is superior to standard genetic algorithm in Web search.
%K search engine
%K Web search
%K Genetic Algorithm (GA)
%K Clonal Selection Algorithm (CSA)
%K Quantum Computing (QC)<br>搜索引擎
%K Web搜索
%K 遗传算法
%K 克隆选择算法
%K 量子计算
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=176D23643BBC7FDBA3FA6CC3914733C4&yid=DE12191FBD62783C&vid=771469D9D58C34FF&iid=E158A972A605785F&sid=5348E91DA94080DE&eid=76C32027E03E49D7&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=13