The relationship between recall and precision
Journal of the American Society for Information Science
Two-stage language models for information retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
The link-prediction problem for social networks
Journal of the American Society for Information Science and Technology
Information Processing and Management: an International Journal
On score distributions and relevance
ECIR'07 Proceedings of the 29th European conference on IR research
Variational bayes for modeling score distributions
Information Retrieval
Web mining based extraction of problem solution ideas
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
One of the best known measures of information retrieval (IR) performance is the F-score, the harmonic mean of precision and recall. In this article we show that the curve of the F-score as a function of the number of retrieved items is always of the same shape: a fast concave increase to a maximum, followed by a slow decrease. In other words, there exists a single maximum, referred to as the tipping point, where the retrieval situation is 'ideal' in terms of the F-score. The tipping point thus indicates the optimal number of items to be retrieved, with more or less items resulting in a lower F-score. This empirical result is found in IR and link prediction experiments and can be partially explained theoretically, expanding on earlier results by Egghe. We discuss the implications and argue that, when comparing F-scores, one should compare the F-score curves' tipping points.