Contents
What does NDCG measure?
NDCG is a measure of ranking quality. In Information Retrieval, such measures assess the document retrieval algorithms. In this article, we will cover the following: Justification for using a measure for ranking quality to evaluate a recommendation engine.
What is NDCG metric?
The NDCG score is simply the ratio of the participant’s DCG score over the ideal ranking’s DCG score i.e: Thus the NDCG metric can be interpreted as the extent to which a user submitted ranking is in agreement with the ideal ranking, taking into account the relevance of each element in that list of things to rank.
How is DCG calculated?
Using a graded relevance scale of documents in a search-engine result set, DCG measures the usefulness, or gain, of a document based on its position in the result list. The gain is accumulated from the top of the result list to the bottom, with the gain of each result discounted at lower ranks.
Why is NDCG sometimes used instead of map?
The primary advantage of the NDCG is that it takes into account the graded relevance values. When they are available in the dataset, the NDCG is a good fit. Compared to the MAP metric it does a good job at evaluating the position of ranked items. It operates beyond the binary relevant/non-relevant scenario.
Why is NDCG sometimes used instead of mAP?
Why is nDCG sometimes used instead of mAP?
What is ranking problem?
Ranking Problems • Rank a set of items and display to users in corresponding order. • Two issues: performance on top and dealing with large search space. – web-page ranking.
How to calculate the Normalized DCG for nDCG?
Now, we calculate our Normalized DCG using the following formula : NDCG metrics does not penalize the bad documents outputs. For Example: [3] and [3, 0, 0] has same NDCG but in second out there are two irrelevent documents.
Why does nDCG not penalize the bad documents outputs?
NDCG metrics does not penalize the bad documents outputs. For Example: [3] and [3, 0, 0] has same NDCG but in second out there are two irrelevent documents. Because no specific standard defined for the number of output documents.
How is NDCG used in a recommendation system?
This is a question about NDCG, which is a recommendation evaluation metric. The following are being used as evaluation indicators for recommendations.
When to use logarithmic reduction factor in Normalized DCG?
But Wang et al. (2013) give theoretical guarantee for using the logarithmic reduction factor in Normalized DCG (NDCG). The authors show that for every pair of substantially different ranking functions, the NDCG can decide which one is better in a consistent manner.