Publication

Offline and online evaluation of news recommender systems at swissinfo.ch

Abstract

We report on the live evaluation of various news recom- mender systems conducted on the website swissinfo.ch. We demonstrate that there is a major diffierence between offine and online accuracy evaluations. In an offine setting, rec- ommending most popular stories is the best strategy, while in a live environment this strategy is the poorest. For online setting, context-tree recommender systems which profile the users in real-time improve the click-through rate by up to 35%. The visit length also increases by a factor of 2.5. Our experience holds important lessons for the evaluation of rec- ommender systems with offine data as well as for the use of the click-through rate as a performance indicator. Copyright © 2014 ACM.

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.