Information Retrieval (IR) deals with the automatic retrieval and ranking of information conveying items, which are relevant to a specific information need. Search engines are the most popular and well-known examples of IR systems. Current evaluation procedures for IR systems mainly focus on the relevance of an item (e.g., Web page) with respect to the user need, but this might not be enough. For example, credibility and correctness should be considered to avoid returning misinformation and potentially harmful content.
This project investigated how to evaluate the performance of IR systems beyond relevance. The first goal was to extend IR evaluation measures to deal with multiple aspects. The second goal was to thoroughly analyze the properties of measures able to account for multiple aspects so that such measures could be integrated in IR systems and lead to better performance.
TBA