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A method for automatic generation of fuzzy membership functions for mobile device's characteristics based on Google Trends

机译：一种基于Google趋势自动生成针对移动设备特征的模糊隶属函数的方法

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摘要

While creating a framework for adaptive mobile interfaces for m-learning applications we found that in order to ease the use of our framework we needed to present the mobile device characteristics to nonexpert users in a easy to understand manner. Using fuzzy sets to represent the characteristics of mobile devices, non-expert developers such as teachers or instructional designers can actively participate in the development or adaptation of the educational tools. To be able to automatically generate the fuzzy membership functions of the sets we needed the data of the mobile device market, regrettably this information is not publicly available. To tackle this problem we have developed a method to estimate the market share of each mobile device based on the popularity metrics recovered from Google Trends and then we use that estimated value as the input to generate the fuzzy set of each characteristic. The proposed method allows us to not only model the state of the market in different periods of time, but also to localize the results to adapt them to the mobile market of specific countries. In this paper we will describe the proposed algorithm and we will discuss the obtained results.
机译：在创建用于m学习应用的自适应移动接口的框架时，我们发现，为了简化我们框架的使用，我们需要以一种易于理解的方式向非专业用户展示移动设备的特性。使用模糊集来表示移动设备的特征，教师或教学设计人员等非专家开发人员可以积极参与教育工具的开发或改编。为了能够自动生成集合的模糊隶属函数，我们需要移动设备市场的数据，很遗憾，此信息尚未公开。为了解决这个问题，我们开发了一种方法，可以根据从Google趋势中获取的流行度指标估算每个移动设备的市场份额，然后将估算值用作输入以生成每个特征的模糊集。所提出的方法使我们不仅可以对不同时期的市场状况进行建模，还可以对结果进行本地化以使其适应特定国家的移动市场。在本文中，我们将描述所提出的算法并讨论获得的结果。

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