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Abstract Bandit algorithms have been widely used in many application areas including information retrieval evaluation and ranking. This is largely due to their exceptional performance. The aim of this study is to examine the overall published studies in terms of trends that shape the use of bandit algorithms in the evaluation and ranking of information retrieval systems. This study also seeks to classify the bandit algorithms used in the research domain. In totality the evaluation metrics, datasets, contribution facets of primary studies as well as the bandit categories are discussed.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |