The Open UniversitySkip to content

Performance measures for multilabel evaluation

Nowak, Stefanie; Lukashevich, Hanna; Dunker, Peter and Rüger, Stefan (2010). Performance measures for multilabel evaluation. In: Proceedings of the international conference on Multimedia information retrieval - MIR '10, p. 35.

Full text available as:
Full text not publicly available (Proof)
Due to publisher licensing restrictions, this file is not available for public download
Click here to request a copy from the OU Author.
DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


With the steadily increasing amount of multimedia documents on the web and at home, the need for reliable semantic indexing methods that assign multiple keywords to a document grows. The performance of existing approaches is often measured with standard evaluation measures of the information retrieval community. In a case study on image annotation, we show the behaviour of 13 different evaluation measures and point out their strengths and weaknesses. For the analysis, data from 19 research groups that participated in the ImageCLEF Photo Annotation Task are utilized together with several configurations based on random numbers. A recently proposed ontology-based measure was investigated that incorporates structure information, relationships from the ontology and the agreement between annotators for a concept and compared to a hierarchical variant. The results for the hierarchical measure are not competitive. The ontology-based results assign good scores to the systems that got also good ranks in the other measures like the example-based F-measure. For concept-based evaluation, stable results could be obtained for MAP concerning random numbers and the number of annotated labels. The AUC measure shows good evaluation characteristics in case all annotations contain confidence values.

Item Type: Conference or Workshop Item
Copyright Holders: 2010 ACM
Keywords: experimentation; performance; measurement
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 25871
Depositing User: Kay Dave
Date Deposited: 06 Jan 2011 11:48
Last Modified: 12 Jun 2020 04:48
Share this page:


Altmetrics from Altmetric

Citations from Dimensions

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU