A Critical Survey on Measuring Success in Rank-Based Keyword Assignment to Documents

Natalie Schluter

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


Evaluation approaches for unsupervised rank-based keyword assignment are nearly as numerous as are the existing systems. The prolific production of each newly used metric (or metric twist) seems to stem from general dissatisfaction
with the previous one and the source of that dissatisfaction has not previously been discussed in the literature. The difficulty may stem from a poor specification of the keyword assignment task in view of the rank-based approach. With a more complete specification of this task, we aim to show why the previous evaluation metrics fail to satisfy researchers’ goals to distinguish and detect good rank-based keyword assignment systems. We put forward a characterisation of an ideal evaluation metric, and discuss the consistency of the evaluation metrics with this ideal, finding that the average standard normalised cumulative gain metric is most consistent with this ideal.
Original languageEnglish
Title of host publicationProc of TALN
PublisherAssociation for Computational Linguistics
Publication date2015
Publication statusPublished - 2015
Externally publishedYes


  • Unsupervised Keyword Assignment
  • Evaluation Metrics
  • Rank-Based Approach
  • Normalised Cumulative Gain
  • Evaluation Consistency


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