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Neuro Fuzzy based user queries categorization

机译:基于神经模糊的用户查询分类

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摘要

With technological advancements the amount of information available in the internet is literally infinite. Gathering of relevant information from internet is a time consuming process. In order to give accurate results to the user, for their search queries, some assistance of the software is needed. Example of such systems is search engines, multi-agent engines, meta-search systems and information filtering systems. So to help user for getting relevant results from a large chunk of data the search engine requires certain information filtering systems which uses various technologies like multi agent, neuro fuzzy etc. This paper presents a fuzzy neural network based approach for query information filtering. The information filtering system has a simple interface for specifying user requests returned from the external search engines and then categorizing them into categories and sub-categories for giving relevant results to the user. The categorization results can be utilized for taking decisions related to service provision.
机译:随着技术的进步,互联网上可用的信息量实际上是无限的。从互联网收集相关信息是一个耗时的过程。为了给用户准确的结果,对于他们的搜索查询,需要软件的一些帮助。这样的系统的例子是搜索引擎,多代理引擎,元搜索系统和信息过滤系统。因此,为了帮助用户从大量数据中获取相关结果,搜索引擎需要某些信息过滤系统,该系统使用多种技术,例如多主体,神经模糊等。本文提出了一种基于模糊神经网络的查询信息过滤方法。信息过滤系统具有一个简单的界面,用于指定从外部搜索引擎返回的用户请求,然后将其分类为类别和子类别,以向用户提供相关结果。分类结果可用于做出与服务提供有关的决策。

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