Abstract
The World Wide Web has provided users with the opportunity to access from any computer the largest set of information ever existing. Researchers have analyzed how such users surf the Web, and such analysis has been used to improve existing services (e.g., by means of data mining and personalization techniques) as well as the generation of new ones (e.g., online targeted advertisement). In recent years, a new trend has developed by which users do not need a computer to access the Web. Instead, the low prices of mobile data connections allow them to access it anywhere anytime. Some studies analyze how users access the Web on their handsets, but these studies use only navigation logs from a specific portal. Therefore, very little attention (due to the complexity of obtaining the data) has been given to how users surf the Web (off-portal) from their mobiles and how that information could be used to build user profiles. This paper analyzes full navigation logs of a large set of mobile users in a developed country, providing useful information about the way those users access the Web. Additionally, it explores how navigation logs can be categorized, and thus user’s interest can be modeled, by using online sources of information such as Web directories and social tagging systems.
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Olmedilla, D., Frías-Martínez, E., Lara, R. (2010). Mobile Web Profiling: A Study of Off-Portal Surfing Habits of Mobile Users. In: De Bra, P., Kobsa, A., Chin, D. (eds) User Modeling, Adaptation, and Personalization. UMAP 2010. Lecture Notes in Computer Science, vol 6075. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13470-8_31
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DOI: https://doi.org/10.1007/978-3-642-13470-8_31
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