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

Abstract: 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 non-expert users in a easy to understand manner. Using fuzzy sets to represent the charact...

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Publicado en:Computers in Human Behavior Vol. 29; no. 2; pp. 510 - 518
Autores principales: Almeida, Aitor, Orduña, Pablo, Castillejo, Eduardo, López-de-Ipiña, Diego, Sacristán, Marcos
Formato: Artículo
Publicado: Elsevier B.V. Mar2013
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2013
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      pub: Elsevier B.V.
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        10.1016/j.chb.2012.06.005
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        atl: A method for automatic generation of fuzzy membership functions for mobile device’s characteristics based on Google Trends
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          Almeida, Aitor
          Orduña, Pablo
          Castillejo, Eduardo
          López-de-Ipiña, Diego
          Sacristán, Marcos
        affil:
          Deusto Institute of Technology – DeustoTech, University of Deusto, Bilbao, Spain
          Treelogic, Llanera, Spain
      su:
        Educational technology
        Economics
        Mobile communication systems
        Mobile learning
        Educational technology research
        Fuzzy sets
        Algorithm research
        Algorithms
        Wireless communications
      sug:
        subj:
          Educational technology
          Economics
          Wireless Telecommunications Carriers (except Satellite)
          Radio and Television Broadcasting and Wireless Communications Equipment Manufacturing
          Mobile communication systems
          Mobile learning
          Educational technology research
          Fuzzy sets
          Algorithm research
          Algorithms
          Wireless communications
      keyword:
        Characterization
        Fuzzy
        Google Trends
        Membership functions
        Mobile devices
        Characterization
        Fuzzy
        Google Trends
        Membership functions
        Mobile devices
      ab: Abstract: 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 non-expert 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.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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