文本挖掘蒙古纳坎用权值(garw)算法生成关联规则,分析网络爬虫

Zulkifli Arsyad
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引用次数: 3

摘要

文本挖掘被广泛用于在大量半结构化和非结构化文本中发现隐藏的模式和信息。文本挖掘从文本数据源中提取有趣的模式来探索知识。关联规则提取GARW(使用加权方案生成关联规则)可用于从web内容集合中查找知识,而无需手动从爬虫的众多搜索结果中读取所有web内容。GARW算法是先验算法的一种发展,用于生成相关的关联规则。这种知识发现的结果可以方便网民从搜索关键词中找到相关信息,而不必逐一查看搜索引擎搜索产生的网页内容。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TEXT MINING MENGGUNAKAN GENERATE ASSOCIATION RULE WITH WEIGHT (GARW) ALGORITHM UNTUK ANALISIS TEKS WEB CRAWLER
Text mining is widely used to find hidden patterns and information in a large number of semi and unstructured texts. Text mining extracts interesting patterns to explore knowledge from textual data sources. Association rule extraction GARW (Generating Association Rule using Weighting Scheme) can be used to find knowledge from a collection of web content without having to read all the web content manually from the many search results of crawlers. The GARW algorithm is a development of a priori to produce relevant association rules. From the results of this knowledge discovery can facilitate netizens users in finding relevant information from search keywords without having to review one by one web content generated from search engine searches.
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