Synonyms
Alpha-nDCG
Definition
α-nDCG is a variant of Normalised Discounted Cumulative Gain (nDCG). It is an evaluation measure for diversified search, where it is assumed that a topic q has multiple possible intents {i}, and that intent probabilities Pr(i|q) and per-intent relevance assessments are available. For a given diversified ranked list, let Ii(r) = 1 if the document at rank r is relevant to intent i and let Ii(r) = 0 otherwise; let \(C_{i}(r)=\sum _{k=1}^{r}I_{i}(k)\). For a given parameter α (typically set to 0.5), let the novelty-biased gain at r be \(\textit {ng}(r)=\sum _{i}I_{i}(r)(1-\alpha )^{C_{i}(r-1)}.\) This reflects the view that (a) the value of a document is basically given by the number of intents it covers; but that (b) for each intent, whenever a relevant document is found, the value of the next relevant document should be discounted (the diminishing return property). α-nDCG at measurement depth (or document cutoff) d is defined as:
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Sakai, T. (2018). α-nDCG. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_80619
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DOI: https://doi.org/10.1007/978-1-4614-8265-9_80619
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