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Traffic Adaptive Optimum Updating Scheme for Search Engines

机译:搜索引擎的流量自适应最佳更新方案

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The increasing complexity, heterogeneity and dynamism of web and its applications have made web information retrieval less recent, less relevant and unmanageable. The search engines face the problem of keeping the contents of its repository consistent with the pages present in the global database using optimum resource utilization. This paper proposes a Traffic Adaptive Optimum updating Scheme (TAOS) to eliminate the needless requests of web crawlers in updating the search engine repository. The scheme also incorporates partial upload of the updated document to the search engine repository. A selfmanaging autonomic computing architecture is proposed to regulate the load on network bandwidth and web servers. The proposed updating scheme is compared for the freshness of search engine repository with the page refresh policies used by web crawlers. The load on network bandwidth and web servers are also analysed for effective resource utilization and is compared with the one consumed during crawler updating.
机译:Web及其应用程序的复杂性,异质性和动态性不断提高,已使Web信息检索的时间越来越短,相关性越来越低且难以管理。搜索引擎面临的问题是,使用最佳资源利用来使其存储库的内容与全局数据库中存在的页面保持一致。本文提出了一种流量自适应最佳更新方案(TAOS),以消除Web爬网程序在更新搜索引擎存储库时不必要的请求。该方案还包括将更新后的文档部分上传到搜索引擎存储库。提出了一种自我管理的自主计算体系结构,以调节网络带宽和Web服务器上的负载。针对Web爬虫使用的页面刷新策略,将建议的更新方案与搜索引擎存储库的新鲜度进行了比较。还分析了网络带宽和Web服务器上的负载以有效地利用资源,并将其与爬网程序更新期间消耗的负载进行比较。

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