EntEEN - Entwicklung von Personalisierten Empfehlungssystemen für Nachrichten; Entwicklung und Evalu
The project investigates how recommendation algorithms contribute to automatically provide relevant news items to readers. The project focuses on three significant aspects of recommendation algorithms. First, we develop an evaluation strategy to accurately measure the system’s utility for its users. Hereby, using implicit feedback as well as uncertainty about user data represents major challenges. Strategies to combine individual recommendation algorithms allows to consider several relevance criteria – such as thematic similarity to previously read articles, trends and other users’ tastes. Such strategies require weighting methods whose optimal parameterization will be analyzed. Hereby, we will apply machine learning methods. Finally, we will examine to what extent preferences in one scenario (e.g., articles about sports) can be used on other scenarios (e.g., articles about economy).
EPEN is a cooperation project of DAI-Labor and plista GmbH and is funded by the Federal Ministry of Economics and Technology.