[u' @incollection{almeida_approach_2013, series = {Communications in {Computer} and {Information} {Science}}, title = {An {Approach} to {Automatic} {Generation} of {Fuzzy} {Membership} {Functions} {Using} {Popularity} {Metrics}}, copyright = {\xa92013 Springer-Verlag Berlin Heidelberg}, isbn = {978-3-642-35878-4 978-3-642-35879-1}, url = {http://link.springer.com/chapter/10.1007/978-3-642-35879-1_66}, abstract = {Creating membership functions for fuzzy system can be a difficult task for non-expert developers. This is even more difficult when the information available about the specific domain is limited. In our case, we wanted to create membership functions that model the different characteristics of mobile devices. Due to the lack of public data about the mobile phones sales it is difficult to estimate the market share of each device. To tackle this problem we have developed a mechanism that uses popularity metrics to estimate the market share and generate the membership functions. In this paper we describe the used algorithm and discuss the obtained results.}, number = {278}, urldate = {2013-09-19}, booktitle = {Information {Systems}, {E}-learning, and {Knowledge} {Management} {Research}}, publisher = {Springer Berlin Heidelberg}, author = {Almeida, Aitor and Ordu\xf1a, Pablo and Castillejo, Eduardo and L\xf3pez-de-Ipi\xf1a, Diego and Sacrist\xe1n, Marcos}, editor = {Lytras, Miltiadis D. and Ruan, Da and Tennyson, Robert D. and Pablos, Patricia Ordonez De and Pe\xf1alvo, Francisco Jos\xe9 Garc\xeda and Rusu, Lazar}, month = jan, year = {2013}, keywords = {Artificial Intelligence, Data analysis, Fuzzy Logic, Google Trends, ISI, Mobile devices, Social Data Mining, WURFL, adaptative interfaces, machine learning, piramide}, pages = {528--533}, } ']