Towards a context-sensitive online newspaper

Jeremy Jancsary, Friedrich Neubarth, Stephanie Schreitter, and Harald Trost
IUI 2011 Workshop on Context-awareness in Retrieval and Recommendation
February 2011, Palo Alto, CA, USA

We give a detailed account of our experiences in implementing a personalized online newspaper that draws – among other hints – on the context of the user. At the algorithmic core of our framework lies a machine learning model that incorporates numerous features of the eligible articles and the user’s current situation. Some of the most important design decisions, however, concern the presentation of suggestions, the collection of explicit and implicit feedback, as well as diversity of the recommendations. We present numerical results obtained during the pilot phase of the project that address a number of these concerns and end with a discussion of open questions and future directions.

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Note:
A journal version of this paper is under preparation.

Please cite as:

@INPROCEEDINGS{Jancsary2011c,
author = {Jeremy Jancsary and Friedrich Neubarth and Stephanie Schreitter and Harald Trost},
title = {Towards a context-sensitive online newspaper},
booktitle = {Proceedings of the 2011 Workshop on Context-awareness in Retrieval and Recommendation},
series = {CaRR ’11},
year = {2011},
}