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首页> 外文会议>International Conference on Human and Social Analytics >An Approach to Web Adaptation by Modelling User Interests Using TF-IDF: A Feature Selection and Multi-Criteria Approach Using AHP
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An Approach to Web Adaptation by Modelling User Interests Using TF-IDF: A Feature Selection and Multi-Criteria Approach Using AHP

机译：使用TF-IDF建模用户兴趣的Web适应方法：使用AHP的特征选择和多标准方法

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摘要

User reviews provide a rich source of information regarding user interests. Many Web platforms allow or even encourage their visitors to leave their feedback regarding the products and services they have consumed. The Term Frequency (TF) and the Inverse Document Frequency (IDF) are two factors that have been used extensively in capturing users' preferences. This paper collects users' reviews from e-tourism Web platforms, calculates the TF and the IDF for each user and adopts a multi-criteria approach in order to quantify users' preferences and dynamically adapt the websites design accordingly. It utilizes the Analytic Hierarchy Process (AHP) and similarity methods in order to determine the relative importance of terms and Web pages and then rearranges them in a new website structure.
机译：用户评论提供有关用户兴趣的丰富信息来源。许多网络平台允许或甚至鼓励他们的访客留下他们对他们所消费的产品和服务的反馈。术语频率（TF）和逆文档频率（IDF）是在捕获用户的偏好方面广泛使用的两个因素。本文从电子旅游Web平台上收集用户评论，计算每个用户的TF和IDF，采用多标准方法，以便量化用户的偏好并相应地动态调整网站设计。它利用分析层次结构（AHP）和相似性方法来确定术语和网页的相对重要性，然后在新的网站结构中重新排列它们。

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