| 基于网页分块的Shark-Search算法 |
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| 引用本文： | 陈军,陈竹敏. 基于网页分块的Shark-Search算法[J]. 山东大学学报(理学版), 2007, 42(9): 62-66 |
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| 作者姓名： | 陈军 陈竹敏 |
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| 作者单位： | 山东大学,网络中心,山东,济南,250100;山东大学,计算机科学与技术学院,山东,济南,250061 |
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| 基金项目： | 国家科技支撑计划子课题;山东省博士学科点专项科研基金 |
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| 摘 要： | Shark-Search算法是一个经典的主题爬取算法. 针对该算法在爬取噪音链接较多的Web页面时性能并不理想的问题, 提出了基于网页分块的Shark-Search算法, 该算法从页面、块、链接的多种粒度来更加有效的进行链接的选择与过滤. 实验证明, 改进的Shark-Search算法比传统的Shark-Search算法在查准率和信息量总和上有了质的提高.
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| 关 键 词： | Shark-Search算法 主题爬取 页面分块 相关性计算沣 |
| 文章编号： | 1671-9352（2007）09-0062-05 |
| 修稿时间： | 2007-06-28 |
Improved Shark-Search algorithm based on page segmentation |
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| CHEN Jun,CHEN Zhu-min. Improved Shark-Search algorithm based on page segmentation[J]. Journal of Shandong University, 2007, 42(9): 62-66 |
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| Authors: | CHEN Jun CHEN Zhu-min |
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| Affiliation: | 1. Network Center, Shandong University, Jinan 250100, Shandong, China; 2. School of Computer Science and Technology, Shandong University, Jinan 250061, Shandong, China |
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| Abstract: | A Shark-Search algorithm is one of the classical algorithms for focused crawling. However, its performance is not ideal for crawling Web pages which contain too many noisy links. An improved Shark-Search algorithm based on page segmentation was proposed, which can accurately evaluate the relevance from three granularities: page, block and single link. Several experiments were carried out to verify that the improved Shark-Search algorithm can obtain significantly higher efficiency than traditional ones. |
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| Keywords: | Shark-Search algorithm focused crawling page segmentation relevance computation |
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