# Is there a paper/article on contextual $\epsilon$-greedy algorithm?

I am reading the paper A Contextual-Bandit Approach to Personalized News Article Recommendation, where it refers to $$\epsilon$$-greedy (disjoint) algorithm. I suspect, that it is just a version of a K-armed bandit with regressors that estimate the average reward for an arm. However, I cannot find the description of this algorithm in the literature (papers, books, or other resources)