基于变异改进粒子群优化算法的聚焦爬虫模型

Guangxia Xu, Peng Jiang, Chuang Ma, M. Daneshmand
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引用次数: 1

摘要

聚焦爬虫是聚焦搜索引擎的关键技术。目前的聚焦爬虫在抓取网页的过程中容易出现适应性差、搜索准确率低等问题。为此,我们提出了一种基于变异改进粒子群优化的聚焦爬虫模型(VRPSOFC)。首先,根据主题相关页面的点击率获得三个种子页面。然后,获得种子页面的四个加权文档。最后,利用基于变异改进粒子群优化算法的聚焦爬虫模型对网页进行抓取,分析结果表明,聚焦爬虫模型在优化精度上有显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Focused Crawler Model Based on Mutation Improving Particle Swarm Optimization Algorithm
The focused crawler is the key technology of the focused search engine. The current focused crawler is prone to poor adaptability and low search accuracy in the process of crawling the webpage. For these reasons, we proposes a focused crawler model (VRPSOFC) based on mutation improving particle swarm optimization. First, get three seed pages based on the click rate of the topic-related page. Then, get the four weighted documents of the seed pages. Finally, using the focused crawler model based on mutation improving particle swarm optimization algorithm to crawl the webpage, the results of the analysis show that the focused crawler model has a significant improvement in the precision of optimization.
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