Modeling consumption of contents and advertising in online newspapers

نویسندگان

  • Iago Porto-Díaz
  • David Martínez-Rego
  • Oscar Fontenla-Romero
  • Amparo Alonso-Betanzos
چکیده

This paper presents the design of a system for personalization of contents and advertising for readers of online newspapers. This software is conceived to work in a context of high network traffic with millions of URLs served each day. The model is divided into two subsystems. The first one takes care of the recommendation of news items. The mathematical model is based on the PageRank algorithm and considers several practical day-to-day scenarios. The second one, which is the subsystem of personalization of advertising, uses a Multinomial Logistic Regression model in order to predict categories of advertising for banners within the news content. The system has obtained practical satisfactory results using

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تاریخ انتشار 2014