An approach to situational market segmentation on on-line newspapers based on current tasks

Authors:
Anne Gutschmidt
Affiliations:
University of Rostock, Rostock, Germany
Venue:
Proceedings of the fourth ACM conference on Recommender systems
Year:
2010

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Abstract

We discuss how a task-based situational market segmentation may be applied to on-line newspapers, distinguishing between fact finding, information gathering and browsing. During a period of four weeks we had 41 users keep a diary and recorded their surfing behavior on different on-line newspapers. The results of a Naive Bayes classification with feature selection indicate that content-related attributes such as the number of news categories browsed are indispensable for task recognition.