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Enhanced data processing using positive negative association mining on AJAX data

机译:在AJAX数据上使用正负关联挖掘进行增强的数据处理

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摘要

Knowledge discovery is the process of analyzing data from different perspectives and summarizing it into useful information. Association rule mining is a data mining process used widely in traditional databases to find the positive association rules. Association rules are created by analyzing data for frequent patterns and by using the criteria support and confidence to identify the most important relationships. However, there are some other challenging rule mining topics like negative association rule mining. In this research, a rule mining approach has been proposed that provides efficient and secure solution using positive and negative association rule computation on Asynchronous JavaScript and XML (AJAX) data. By using AJAX, we get the search result in the form of semantic data. Whenever data search from database is intended, the next possible word of the search will be made available.
机译:知识发现是从不同角度分析数据并将其汇总为有用信息的过程。关联规则挖掘是在传统数据库中广泛使用的数据挖掘过程,用于查找肯定的关联规则。通过分析频繁模式的数据并使用标准支持和置信度来确定最重要的关系,从而创建关联规则。但是,还有其他一些具有挑战性的规则挖掘主题,例如否定关联规则挖掘。在这项研究中,已经提出了一种规则挖掘方法,该方法使用对异步JavaScript和XML(AJAX)数据的正负关联规则计算来提供有效且安全的解决方案。通过使用AJAX,我们以语义数据的形式获得搜索结果。每当打算从数据库进行数据搜索时,下一个可能的搜索词将变为可用。

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