WSOLINK: web structure outlier detection algorithm

Rachna Miglani
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引用次数: 0

Abstract

In this world of specialisation where everything is getting specialised, data warehouses and web mining techniques are also getting specialised. Web usage mining, web content mining, and web structure mining are various categories of web mining techniques depending upon the data to be mined. Apriori algorithm, FP growth algorithm, and average linear time algorithm are available to analyse the general access patterns in web server logs whereas WCOND-mine and signed with weight technique are web content outlier mining algorithms. However, no such algorithm is available to check the authenticity and availability of hyperlinks in the resultant web pages given by web search engines. The present research work aims at detection of outliers from the results of queries over web pages through web search engines.
WSOLINK: web结构离群点检测算法
在这个一切都变得专业化的世界里,数据仓库和网络挖掘技术也变得专业化。Web使用挖掘、Web内容挖掘和Web结构挖掘是Web挖掘技术的不同类别,这取决于要挖掘的数据。Apriori算法、FP增长算法和平均线性时间算法可用于分析web服务器日志中的一般访问模式,而WCOND-mine和signed with weight技术是web内容离群值挖掘算法。然而,没有这样的算法是可用的,以检查的真实性和可用性的结果网页上的超链接由网络搜索引擎给出。目前的研究工作旨在通过网络搜索引擎从网页查询结果中检测异常值。
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