| 基于Web页面平均质量的Web搜索模型和优化算法 |
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| 引用本文： | 付国瑜,黄贤英.基于Web页面平均质量的Web搜索模型和优化算法[J].计算机应用,2009,29(4):1114-1116. |
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| 作者姓名： | 付国瑜 黄贤英 |
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| 作者单位： | 重庆工学院,计算机科学与工程学院,重庆,400050 |
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| 摘 要： | 针对Web搜索引擎的特点，提出了一种基于量子遗传克隆挖掘(QGCMA)的搜索策略。该算法将用户的查询描述为Web页面的平均质量，并通过克隆，变异，交叉的操作获取具有高亲和度的抗体（Web页面）。通过实验结果分析得出，在Web搜索中该方法比标准的遗传算法(GA)具有较明显的优势。
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| 关 键 词： | 搜索引擎 Web搜索 遗传算法 克隆选择算法 量子计算 |
| 收稿时间： | 2008-10-27 |
| 修稿时间： | 2008-12-07 |
Web search model and optimal algorithm based on mean quantity of Web pages |
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| FU Guo-yu,HUANG Xian-ying.Web search model and optimal algorithm based on mean quantity of Web pages[J].journal of Computer Applications,2009,29(4):1114-1116. |
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| Authors: | FU Guo-yu HUANG Xian-ying |
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| Affiliation: | School of Computer Science and Engineering;Chongqing Institute of Technology;Chongqing 400050;China |
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| Abstract: | 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. |
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| Keywords: | search engine Web search Genetic Algorithm (GA) Clonal Selection Algorithm (CSA) Quantum Computing (QC) |
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