Abstract
e-tourism is in stable growth and becoming one of the leading sectors in the e-commerce world. Social media and mobile technologies are holding an increasingly important role in the procurement processes of tourism, by both providing access to real-time information and promoting the exchange of experiences. Web mining allows the collection of new unstructured data and the building of users’ profiles based on electronic web mouth. We apply a soft approach to solve lexical ambiguity and build a vocabulary for the tourism sector. Indeed, we propose a new version of the fuzzy c-means algorithm to detect the best centroid clusters, and we choose the final partition according to the validation of three indices (the partition coefficient, the classification entropy, and the Xie-Beni index). We use this method to classify 525 posts published by the Italian tourism forum from January 2010 to April 2012.
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Iezzi, D.F., Mastrangelo, M. (2014). Fuzzy c-Means for Web Mining: The Italian Tourist Forum Case. In: Vicari, D., Okada, A., Ragozini, G., Weihs, C. (eds) Analysis and Modeling of Complex Data in Behavioral and Social Sciences. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-06692-9_17
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DOI: https://doi.org/10.1007/978-3-319-06692-9_17
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