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Discovery of user profiles using fuzzy web intelligent techniques

机译:使用模糊Web智能技术发现用户资料

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With the dramatically quick and explosive growth of information available over the internet, World Wide Web has become a powerful platform to store, disseminate and retrieve information as well as mine useful knowledge. Web usage mining addresses the application of data mining techniques over web data in order to identify and characterise users' navigation behaviour patterns. The wide spectrum of uncertainties involved in the web navigation process can be modelled and handled using fuzzy set theory. Fuzzy web intelligent techniques are used in this paper to deal with uncertainty in web navigation patterns and for uncovering web user communities. Intelligent fuzzy clustering algorithm (1FC) is proposed in this work and the performance of IFC is compared with popular fuzzy C-means algorithm (FCM) and functional fuzzy C-means (FFCM) algorithm.
机译:随着Internet上信息的迅猛增长,万维网已经成为存储,传播和检索信息以及挖掘有用知识的强大平台。 Web使用挖掘解决了数据挖掘技术在Web数据上的应用,以识别和表征用户的导航行为模式。可以使用模糊集理论对网络导航过程中涉及的各种不确定性进行建模和处理。本文使用模糊Web智能技术来处理Web导航模式中的不确定性以及发现Web用户社区。提出了智能模糊聚类算法(1FC),并将IFC的性能与流行的模糊C-均值算法(FCM)和功能性模糊C-均值算法(FFCM)进行了比较。

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