ImprovingWeb Searches with Distributed Buckets Structures

V. Gil-Costa, A. M. Printista, Mauricio Marín
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引用次数: 2

Abstract

This article compares several strategies for searching in Web engines and we present the bucket algorithms to improve the efficiency of a classical index data structure for parallel textual database. We use the inverted files as the data structure and the vector space model to perform the ranking of documents. The main interest is the queries parallel processing on a cluster of PCs, and therefore this paper is focused in the communication and synchronization optimization. The design of the server that processes the queries, is effected on top of the bulk synchronous-BSP model of parallel computing, to study how query performance is affected by the index organization
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用分布式桶结构改进web搜索
本文比较了Web引擎中的几种搜索策略,并提出了桶算法来提高并行文本数据库的经典索引数据结构的效率。我们使用倒排文件作为数据结构,并使用向量空间模型对文档进行排序。本文主要研究的是pc机集群上的查询并行处理问题,因此本文主要研究通信和同步优化问题。处理查询的服务器的设计在并行计算的批量同步- bsp模型的基础上进行,以研究索引组织如何影响查询性能
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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Semantic Contexts in the Internet Recycling Course Web Pages for the Semantic Web ImprovingWeb Searches with Distributed Buckets Structures Contextual Entropy and Text Categorization Preserving the Scholarly Side of the Web
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