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arXiv · 2212.00492

Principled Multi-Aspect Evaluation Measures of Rankings

Maria Maistro·Lucas Chaves Lima·Jakob Grue Simonsen·Christina Lioma
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Abstract

Information Retrieval evaluation has traditionally focused on defining principled ways of assessing the relevance of a ranked list of documents with respect to a query. Several methods extend this type of evaluation beyond relevance, making it possible to evaluate different aspects of a document ranking (e.g., relevance, usefulness, or credibility) using a single measure (multi-aspect evaluation). However, these methods either are (i) tailor-made for specific aspects and do not extend to other types or numbers of aspects, or (ii) have theoretical anomalies, e.g. assign maximum score to a ranking where all documents are labelled with the lowest grade with respect to all aspects (e.g., not relevant, not credible, etc.). We present a theoretically principled multi-aspect evaluation method that can be used for any number, and any type, of aspects. A thorough empirical evaluation using up to 5 aspects and a total of 425 runs officially submitted to 10 TREC tracks shows that our method is more discriminative than the state-of-the-art and overcomes theoretical limitations of the state-of-the-art.

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Maria Maistro, Lucas Chaves Lima, Jakob Grue Simonsen, Christina Lioma. 2022-12-01. Principled Multi-Aspect Evaluation Measures of Rankings. https://doi.org/10.1145/3459637.3482287

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