Abstract
Insights into the behavior and preference of mobile device users from their web browsing/application activities are critical components of any successful dynamic content recommendation system, mobile advertisement platform, or web personalization initiative. In this paper we use an unsupervised topic model to understand the interests of the cellular users based upon their browsing profile. We posit that the length of time a user remains on a given website is positively correlated with the user’s interest in the website’s content. We propose an extended model to integrate this duration information efficiently by oversampling the URLs.
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Giri, R., Choi, H., Hoo, K.S., Rao, B.D. (2014). User Behavior Modeling in a Cellular Network Using Latent Dirichlet Allocation. In: Corchado, E., Lozano, J.A., Quintián, H., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2014. IDEAL 2014. Lecture Notes in Computer Science, vol 8669. Springer, Cham. https://doi.org/10.1007/978-3-319-10840-7_5
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DOI: https://doi.org/10.1007/978-3-319-10840-7_5
Publisher Name: Springer, Cham
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